Method and apparatus for detecting and discriminating tachycardia in a subcutaneously implantable cardiac device

ABSTRACT

A medical device and associated method for discriminating cardiac events includes sensing a cardiac signal spatially located across approximately a full duration of a predetermined sensing window. A match score is determined corresponding to the sensed cardiac signal. A beat feature of multiple beat features across less than the full duration of the sensing window is determined, the beat feature being selected from the multiple beat features in response to the match score. Cardiac event evidence is accumulated in response to the match score and the determined beat feature, and cardiac events are discriminated in response to the accumulated cardiac evidence.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.12/768,773, now abandoned, filed Apr. 29, 2010, entitled “METHOD ANDAPPARATUS FOR DETECTING AND DISCRIMINATING TACHYCARDIA” which isincorporated herein by reference in its entirety.

TECHNICAL FIELD

The disclosure relates generally to implantable medical devices and, inparticular, to a method and apparatus for discriminatingsupraventricular tachycardia (SVT) from ventricular tachycardia (VT).

BACKGROUND

A typical implantable cardioverter defibrillator (ICD) has thecapability of providing a variety of anti-tachycardia pacing (ATP)regimens as well as cardioversion/defibrillation shock therapy.Normally, arrhythmia therapies are applied according to a pre-programmedsequence of less aggressive to more aggressive therapies depending onthe type of arrhythmia detected. Typically, termination of an arrhythmiais confirmed by a return to either a demand-paced rhythm or a sinusrhythm in which successive spontaneous R-waves are separated by at leasta defined interval. When ATP attempts fail to terminate the tachycardia,high-voltage cardioversion shocks may be delivered. Since shocks can bepainful to the patient and consume relatively greater battery chargethan pacing pulses, it is desirable to avoid the need to deliver shocksby successfully terminating the tachycardia using less aggressive pacingtherapies.

The success of a tachycardia therapy depends in part on the accuracy ofthe tachycardia detection. In some cases, a tachycardia originating inthe atria, i.e. a supraventricular tachycardia (SVT), is difficult todistinguish from a tachycardia originating in the ventricles, i.e. aventricular tachycardia (VT). For example, both the atrial chambers andthe ventricular chambers may exhibit a similar tachycardia cycle lengthwhen an SVT is conducted to the ventricles, or when a VT is conductedretrograde to the atria. Accordingly, methods are needed for accuratelyclassifying a detected tachycardia as being either a VT or an SVT eventto allow the most appropriate therapy to be delivered by the ICD, withthe highest likelihood of success and without unacceptably delayingattempts at terminating the tachycardia.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic representation of an implantable medical device(IMD).

FIG. 2 is a functional block diagram of the IMD shown in FIG. 1according to one embodiment.

FIG. 3 is a state diagram of operating states included in a tachycardiadetection and discrimination algorithm.

FIG. 4 is a flow chart of operations performed in State 1 of thetachycardia detection algorithm.

FIG. 5 is a flow chart of a sudden heart rate change detector thatoperates during a low RR interval variability mode of State 1.

FIG. 6 is a plot of the expected RR interval range computed using RRMEANand RRMAD metrics of RR intervals (RRIs).

FIG. 7 is a flow chart of a method for controlling switching between lowRRI variability and high RRI variability modes of operation during State1.

FIG. 8 is a flow chart of operations performed by the sudden RRIvariability change detector during the high variability mode.

FIG. 9 is a flow chart of one method for comparing heart rate estimatesobtained from two different sensing vectors.

FIG. 10 is a flow chart providing an overview of operations performedduring State 2 of the detection algorithm.

FIG. 11 is a flow chart of a method for discriminating between VT(treatable) and SVT (non-treatable) rhythms during State 2 operations.

FIG. 12 is a flow chart of one method for extracting specific beatfeatures and accumulating VT evidence on a beat-by-beat basis.

FIG. 13A is a flow chart of the application of an SVT confident zonebeat feature rule.

FIG. 13B is a flow chart of one method for applying a VT beat rule whenan overall morphology score falls into the SVT gray zone.

FIG. 13C is a flow chart of one method for applying VT gray zone beatfeature rules.

FIG. 14 is a flow chart of a method for applying rules across multipleoverall morphology score gray zones.

FIG. 15 is a flow chart of a process for applying a rule for detecting arhythm breaking point.

FIG. 16 is a flow chart of one method for applying a rule for detectinga rhythm breaking point across the whole SVT morphology score zone.

FIG. 17 is a flow chart of a process for adjusting a VT evidence counteron a beat-by-beat basis in response to morphology score zone rules.

FIG. 18 is a flow chart of a method for classifying a current beat as acorrupted or non-corrupted signal in a noise/artifact rejection process.

FIG. 19 is a flowchart of one method for computing metrics of noise,such as lead-related artifact, for use in classifying an EGM signal ascorrupted or non-corrupted.

FIG. 20 is a flowchart of a method for transitioning between detectionalgorithm states.

FIG. 21 is a flow chart of a post-therapy mode of operation performedupon re-entering State 2 after delivering a tachycardia therapy.

FIG. 22 is a flow chart of one method for detecting post-therapy VTtermination according to one embodiment.

FIG. 23 is a flow chart of one method for redetecting VT during a posttherapy mode of operation.

DETAILED DESCRIPTION

In the following description, references are made to illustrativeembodiments. It is understood that other embodiments may be utilizedwithout departing from the scope of the disclosure. In some instances,for purposes of clarity, identical reference numbers may be used in thedrawings to identify similar elements. As used herein, the term “module”refers to an application specific integrated circuit (ASIC), anelectronic circuit, a processor (shared, dedicated, or group) and memorythat execute one or more software or firmware programs, a combinationallogic circuit, or other suitable components that provide the describedfunctionality.

A tachycardia detection algorithm for detecting and discriminatingbetween treatable and non-treatable rhythms is disclosed. The term“treatable rhythm”, as used herein, refers to any tachycardia that isventricular in origin and can potentially be treated by delivering atherapy in the ventricles for terminating the ventricular tachycardiasuch as anti-tachycardia pacing or ventricular cardioversion ordefibrillation shocks. A “non-treatable” rhythm is any rhythm with arelatively slow ventricular rate (below a ventricular tachycardia rate)and any tachycardia that is supraventricular in origin. Delivering atherapy only in the ventricular chambers frequently does not resolve asupraventricular tachycardia.

As used herein, a “concerning rhythm” is any heart rhythm that meetscriteria to transition from an unconcerned detection state to aconcerned detection state for detecting a potentially treatable rhythm.The criteria for transitioning to a concerned detection state may varybetween embodiments but typically includes detecting rhythms that areeither a fast enough ventricular rate to potentially be a treatabletachycardia, or rhythms that have a sudden change in the heart rhythmthat could be associated with VT, e.g. an abrupt increase in theventricular rate or an abrupt decrease in RR interval (RRI) variability.

VT refers inclusively to any fast ventricular rhythm meeting detectioncriteria as described herein and does not exclude ventricularfibrillation (VF) unless explicitly stated. In the illustrativeembodiment described herein, the detection algorithm relies on variousheart rate limits for detecting and discriminating VT and SVT. A“detection lower limit” is the heart rate below which a treatabletachycardia cannot be detected. The ventricular rate must be faster thanthe detection lower rate limit (or the RRI shorter than the associateddetection lower limit interval) in order to detect a treatable rhythm.An SVT limit is the heart rate above which the rhythm is classified as aVT and is identified as a treatable rhythm. A ventricular rate fasterthan the SVT rate limit (or RRIs shorter than the SVT limit interval) isconsidered to be too fast to be supraventricular in origin. For example,in one embodiment a nominal value for the detection lower limit intervalis approximately 400 ms and a nominal value of the SVT limit interval isapproximately 240 ms. A heart rate characterized by RRIs longer than thedetection lower limit is not likely to be a concerning rhythm. A heartrate characterized by RRIs shorter than the detection lower limit butlonger than the SVT limit may be a concerning rhythm depending on otherfactors. A heart rate characterized by RRIs shorter than the SVT limitinterval may be detected as VT.

FIG. 1 is a schematic representation of an implantable medical device(IMD) 10. IMD 10 is embodied as an ICD in FIG. 1. Methods describedherein, however, should not be interpreted as being limited to anyparticular implantable medical device or any particular cardiac medicaldevice. Instead, embodiments may include any cardiac medical device solong as the device utilizes a plurality of electrodes or other sensorsfor monitoring the cardiac rhythm of a patient. The electrodes arecapable of sensing cardiac EGM or ECG signals, referred to hereincollectively as “cardiac signals”.

In FIG. 1, the right atrium (RA), left atrium (LA), right ventricle(RV), left ventricle (LV), and the coronary sinus (CS), extending fromthe opening in the right atrium to form the great cardiac vein, areshown schematically in heart 12. Two transvenous leads 16 and 18 connectIMD 10 with the RV and the LV, respectively. Each lead includes at leastone electrical conductor and pace/sense electrode. For example, leads 16and 18 are respectively connected to pace/sense electrodes 20, 22, and24, 28. In addition, a housing electrode 26 can be formed as part of theouter surface of the housing of the device 10. The pace/sense electrodes20, 22, and 24, 28 and housing electrode 26 can be selectively employedto provide a number of unipolar and bipolar pace/sense electrodecombinations for pacing and sensing functions. The depicted positions inor about the right and left heart chambers are merely illustrative.Moreover, other leads and pace/sense electrodes can be used instead of,or in combination with, any one or more of the depicted leads andelectrodes.

Typically, in pacing systems of the type illustrated in FIG. 1, theelectrodes designated herein as “pace/sense” electrodes are used forboth pacing and sensing functions. In certain embodiments, theseelectrodes can be used exclusively as pace or sense electrodes inprogrammed or default combinations for sensing cardiac signals anddelivering pace pulses. The leads and electrodes described can beemployed to record cardiac signals. The recorded data can beperiodically transmitted to a programmer or other external deviceenabled for telemetric communication with the IMD 10.

An RV coil electrode 34 and a superior vena cava (SVC) coil electrode 32are also shown as being coupled to a portion of RV lead 16. Coilelectrodes can additionally or alternatively be coupled to portions CSlead 18. The coil electrodes 32 and 34, or other similar electrodetypes, can be electrically coupled to high voltage circuitry fordelivering high voltage cardioversion/defibrillation shock pulses.

Electrodes shown in FIG. 1 can be disposed in a variety of locations in,around, and on the heart and are not limited to the locations shown.Furthermore, other lead and electrode systems may be substituted for thesystem shown in FIG. 1. The detection algorithm described herein doesnot require the use of electrodes for sensing atrial signals fordetecting and discriminating treatable rhythms. As such, IMD 10 is showncoupled only to ventricular leads 16 and 18 but implementation of thedetection algorithm is not limited to systems employing only ventricularleads. In other embodiments, dual chamber or multi-chamber systems maybe used which include atrial leads used to position electrodes in, on oraround the atrial chambers.

ICDs and pacemakers typically use a single ventricular EGM signal forsensing ventricular events (R-waves) for determining a need for pacingand for detecting a RR intervals meeting tachycardia detection criteria.An EGM sensing vector may be a unipolar or bipolar sensing vector usingone or two electrodes, respectively, placed in or on the ventricularheart chambers. Sensing errors that may occur on a single ventricularEGM signal may result in unneeded therapies being delivered by the ICD.Typical sensing errors that may occur include oversensing of T-waves,electromagnetic interference, non-cardiac myopotential noise,lead-related artifact, or other non-physiologic noise and double sensingof a single QRS complex. Sensing errors, including undersensing of truedepolarizations and oversensing of T-waves, may also occur as a resultof delivering pacing energy from the same electrodes that are used forsensing.

The tachycardia detection algorithm described herein employssimultaneous dual-vector EGM sensing for use in estimating a heart rateand for applying rules on a beat-by-beat basis to accumulate evidence ofVT for the detection of treatable rhythms. One sensing vector isselected to provide an EGM signal having a relatively global EGM signal,also referred to herein as the far-field (FF) signal in that at leastone of the sensing electrodes is placed away from the ventricularchambers to obtain a signal representing the spatial summation of actionpotential signals as they occur over a larger area of the ventricles.The second sensing vector is selected to provide an EGM signal having arelatively more local EGM signal, also referred to herein as thenear-field (NF) signal in that both electrodes are typically located inor on a ventricular chamber to obtain a more local ventricular EGMsignal (smaller area of spatial summation of action potential signals).

In the illustrative embodiment shown in FIG. 1, a FF signal may beobtained by using any of the electrodes 20, 22, 24, 28, and 34 locatedwithin or on the ventricles paired with any electrode located away fromthe ventricles, such as SVC coil electrode 32 or the housing electrode26. A near field signal may be obtained by selecting any two of theelectrodes 20, 22, 24, 28 and 34 located within the ventricles in abipolar pair. For example, a NF EGM signal may be sensed between the RVtip electrode 22 and the RV ring electrode 20. A FF EGM signal may besensed simultaneously with the NF EGM signal using the RV coil electrode34 and the housing electrode 26.

It is desirable to sense the FF and NF EGM signals using two distinctsensing vectors that do not share a common electrode. Depending on theelectrode and lead configuration used, however, some embodiments mayemploy a common electrode between the two simultaneously sensed EGMsignals. The tachycardia detection algorithm described herein refers tothe use of a FF EGM signal and a NF EGM signal, however, in alternativeembodiments any two distinct sensing vectors, with or without a commonelectrode, may be used, including any combination of at least two FFsignals, at least two NF signals, or a combination including one FF andone NF signal.

Embodiments described herein are not limited to use with intracardiac ortransvenous leads. Subcutaneously implanted electrodes or even externalelectrode systems may be used. In these cases, a “near-field” signal maybe obtained by bipoles spaced more closely together than a second pairof electrodes separated by a relatively greater distance for obtaining a“far-field” signal.

FIG. 2 is a functional block diagram of the IMD 10 shown in FIG. 1according to one embodiment. IMD 10 generally includes timing andcontrol circuitry 52 and a controller that may be embodied as amicroprocessor 54 or a digital state machine for timing sensing andtherapy delivery functions in accordance with a programmed operatingmode. Microprocessor 54 and associated memory 56 are coupled to thevarious components of IMD 10 via a data/address bus 55. IMD 10 includestherapy delivery module 50 for delivering electrical stimulation pulsesto a patient's heart including cardiac pacing pulses, arrhythmia pacingtherapies such as anti-tachycardia pacing (ATP) andcardioversion/defibrillation shocks, under the control of timing andcontrol 52 and microprocessor 54. Therapy delivery module 50 istypically coupled to two or more electrodes 68 via an optional switchmatrix 58. Electrodes 68 correspond to the various electrodes shown inFIG. 1. Switch matrix 58 is used for selecting which electrodes andcorresponding polarities are used for delivering electrical stimulationpulses.

Cardiac electrical signals are sensed for determining when an electricalstimulation therapy is needed and in controlling the timing ofstimulation pulses. Electrodes used for sensing and electrodes used forstimulation may be selected via switch matrix 58. When used for sensing,cardiac signals received by electrodes 68 are coupled to signalprocessing circuitry 60 via switch matrix 58. Signal processor 60includes sense amplifiers and may include other signal conditioningcircuitry such as filters and an analog-to-digital converter. Cardiacelectrical signals may then be used by microprocessor 54 for detectingphysiological events, such as detecting and discriminating cardiacarrhythmias. Signal processing circuitry 60 includes cardiac eventsensing circuitry for sensing ventricular events, i.e. R-waves, for usein determining RRIs and QRS waveform morphology.

A tachycardia detection algorithm is implemented by the IMD controllerfor detecting and discriminating treatable and non-treatable rhythms.Sensed ventricular event intervals (RRIs) and R-wave morphology are usedin detecting and discriminating VT from SVT. A determination as towhether the heart rhythm is a treatable rhythm can be made based onventricular EGM signals without requiring the use of atrial signals.

In response to detecting a treatable rhythm, a therapy is delivered bytherapy delivery module 50 under the control of timing and control 52.The therapy may be delivered according to a programmed menu oftherapies. Arrhythmia therapies may include a menu of tiered therapiesin which less aggressive ATP regimens are delivered first and, when notsuccessful, a high voltage shock therapy is delivered.

IMD 10 may additionally be coupled to one or more physiological sensors70 carried by leads extending from IMD 10 or incorporated in or on theIMD housing. Signals from sensors 70 are received by a sensor interface62 which provides sensor signals to signal processing circuitry 60.Sensor signals may be used by microprocessor 54 for detectingphysiological events or conditions.

The operating system includes associated memory 56 for storing a varietyof programmed parameter values that are used by microprocessor 54. Thememory 56 may also be used for storing data compiled from sensed EGM/ECGand other physiological signals and/or relating to device operatinghistory for telemetry out on receipt of a retrieval or interrogationinstruction. Parameters and tachycardia discrimination rules andalgorithms may be stored in memory 56 and utilized by microprocessor 54.

IMD 10 further includes telemetry circuitry 64 and antenna 65.Programming commands or data are transmitted during uplink or downlinktelemetry between ICD telemetry circuitry 64 and external telemetrycircuitry included in a programmer or monitoring unit.

FIG. 3 is a state diagram 100 illustrating operating states that may beincluded in a tachycardia detection and discrimination algorithm. Thetachycardia detection algorithm includes four operating states 102, 104,106 and 108. State 1 102 is an unconcerned state corresponding to astate in which RRI monitoring is occurring. An analysis of RRIs isperformed to detect a sudden change in the heart rhythm. A sudden changemay be a sudden change in heart rate (HR), i.e. a sudden change in thelength of RRIs, or a sudden change in RRI variability, i.e. a suddenchange in RRI differences. A HR change detector and a RRI variabilitychange detector operate in State 1 102 and will be described in detailbelow.

A transition to State 2 104, the concerned state, occurs when eithersudden change detection criteria or high heart rate criteria applied tomeasured RRIs are met in State 1 102. A transition from State 1 to State2 occurs based on RRI monitoring without performing additionalmorphology analysis. In order to enter State 2 104, an increase in HRhas been detected in State 1 104, such that RRIs that are shorter thanthe detection lower limit interval have been measured. State 2 104 is a“concerned state” because the HR is increased but the heart chamber thatthe fast ventricular rate is originating in may be uncertain. Additionalanalysis is needed to discriminate between SVT and VT. During State 2,evidence of VT is accumulated on a beat-by-beat basis using morphologyanalysis of the ventricular EGM signals. The morphology analysis is usedin addition to the RRI analysis to determine if the rhythm is a“treatable” VT rhythm or “non-treatable” rhythm.

Transition out of State 2, either back to State 1 (unconcerned) orforward to State 3 (convinced) can occur based on RRI data alone or acombination of RRI data and EGM signal morphology data. As such, inState 2 104, RRI monitoring continues and additional monitoring of EGMsignal morphology is performed to accumulate evidence of VT on abeat-by-beat basis as will be described in detail herein. If RRIcriteria and VT evidence satisfies VT detection criteria, a transitionto State 3 106 occurs. If RRI criteria and/or VT evidence no longer meetthe criteria required to remain in State 2, a transition back to State 1102 occurs.

Once State 3 106 is reached, VT is detected and a therapy selectionprocess begins, e.g. according to a programmed menu of therapies.However, since the onset of the therapy may be delayed due to capacitorcharging, a programmed therapy delay, or other reasons, the IMD controlsystem may remain in State 3 for an interval of time. RRI monitoring andmorphology analysis performed in State 2 continues in State 3.

A transition from State 3 106 directly to State 1 102 can occur if theRRI data indicates that the HR falls below a concerning rate, i.e. belowthe detection lower rate limit. A transition to State 2 104 may occur ifRRI data or morphology analysis no longer satisfy VT detection criteriabut remain above a threshold for the concerned state.

A transition from State 3 106 to State 4 108 occurs when a pendingtherapy is ready for delivery. For example, a therapy delay, capacitorcharging or other time interval leading up to actual therapy onsetexpires and a transition to State 4 is made. Therapy is delivered inState 4. After therapy delivery, a transition back to state 2 104 occursto continue monitoring the heart rhythm. The detection anddiscrimination algorithm remains in State 2 104 until reaching adecision to return to State 1 102 or to State 3 106 based on RRIcriteria and morphology analysis. The various state transitions andoperations performed within each detection algorithm state will now bedescribed in greater detail.

FIG. 4 is a flow chart 150 of operations performed in State 1 of thetachycardia detection algorithm. Flow chart 150 and other flow chartsshown herein are intended to illustrate the functional operation of thedevice, and should not be construed as reflective of a specific form ofsoftware or hardware necessary to practice the methods described. It isbelieved that the particular form of software, firmware and/or hardwarewill be determined primarily by the particular system architectureemployed in the device and by the particular detection and therapydelivery methodologies employed by the device. Providing software,firmware and/or hardware to accomplish the described functionality inthe context of any modern medical device, given the disclosure herein,is within the abilities of one of skill in the art.

Methods described in conjunction with flow charts presented herein maybe implemented in a computer-readable medium storing instructions forcausing a programmable processor to carry out the methods described. A“computer-readable medium” includes but is not limited to any volatileor non-volatile media, such as a RAM, ROM, CD-ROM, NVRAM, EEPROM, flashmemory, and the like. The instructions may be implemented as one or moresoftware modules, which may be executed by themselves or in combinationwith other software.

State 1 is entered at block 151 either upon initialization of the IMD orafter returning to State 1 from State 2 or State 3. Both FF and NF EGMsignals are sensed at block 152. A dual vector sensing approach is usedto allow confirmation of a detected heart rate using a second EGM signalbefore a state transition occurs. The dual vector sensing approach alsoallows for selective analysis of the overall signal morphology within ananalysis window and/or analysis of specific features of the FF and NFsignals within the analysis window, referred to herein as “beatfeatures”, to be performed in manner that provides the highestseparation of SVT and VT when operating in States 2 and 3.

When sensing the NF and the FF EGM signals, the NF sensing electrodepair may also be used for delivering pacing pulses to the heart. If noventricular pacing pulse is delivered (as determined at decision block153), the next NF and FF events are sensed at block 156. A NF HR and aFF HR are determined at block 157 using the respective NF and FF RRIsmeasured between the currently NF/FF sensed event and the previous NF/FFsensed event, respectively.

As will become apparent from the illustrative embodiment described indetail herein, the NF EGM signal can be considered the “primary” sensingsignal because the NF signal is used for sensing cardiac events formeasuring RRIs for estimating the HR, detecting a sudden change in theheart rhythm during State 1 operations, and for setting a morphologyanalysis window during State 2 operations. Analysis of the FF EGM signalis “secondary” in that the FF EGM signal is used to verify a NF heartrate and for morphology analysis in State 2 after a concerning rhythm isidentified.

As such, in some embodiments, identifying sensed events and measuringintervals between sensed events on the FF EGM signal may be delayed intime relative to NF event sensing. The cardiac events may be sensed andRRIs may be measured in real time on the NF EGM signal. The FF EGMsignal may be analyzed in real-time simultaneously with the NF EGMsignal or buffered for later analysis. Searching for FF sensed eventsusing the buffered signal may be performed retrospectively upondetermining a need to verify the outcome of the NF signal analysis. Aretrospective analysis of a stored FF EGM signal for sensing R-waves maybe more accurate than real-time sensing of cardiac events.

If a ventricular pacing pulse is delivered as determined at block 153,the FF EGM signal is “forced” to “sense” a cardiac event. A FF eventmarker is automatically generated at block 154 for use in measuring RRIsfor estimating a FF HR at block 156 for the current heart beat.Additionally, the FF sense threshold is set at block 155 in preparationfor sensing the next FF event. Normally, an auto-adjusting sensingthreshold will track the amplitude of a sensed event and decaythereafter. Since a pacing pulse causes an automatically-generated“sense” event on the FF signal, an alternative method for setting anauto-adjusting sense threshold is used when a pacing pulse is delivered.

When a pacing pulse is delivered, the automatically-generated FF eventmarker is followed by a blanking period. The FF sensing threshold thentracks the amplitude of the evoked response throughout the FF EGMblanking period but no new events are sensed during the blanking period.When the blanking period expires, the FF sensing threshold is set to apercentage of the peak amplitude tracked during the blanking period atblock 155. The FF sensing threshold thereafter decays over time untilanother pacing pulse is delivered or until an intrinsic event is sensedon the FF EGM signal.

A NF HR and a FF HR are measured at block 157 using respective NF and FFRRIs measured between sensed events. If the NF HR is greater than asudden change limit, as determined at block 158, and the NF and FF HRsapproximately match (block 168), a transition to State 2 occurs at block170. The sudden change limit used at block 158 is a threshold heart rateor corresponding RRI falling between the detection lower rate limit andthe SVT limit. A heart rate greater than the sudden change limit (or RRIshorter than the sudden change limit interval) is identified as a“concerning rhythm” without requiring a sudden change in the heartrhythm to be detected. Specifically, the detection algorithm does notrequire observation of a sudden change in HR or in RRI variability inorder to identify a concerning rhythm. For example, a sudden changelimit might be a HR of 190 beats per minute (bpm). Above 190 bpm, nosudden change detection requirements are needed to change from State 1to State 2 because the very high HR itself is considered a concerningheart rhythm.

In order to compare the current HR to a HR threshold, such as the suddenchange limit or the detection lower limit, SVT limit or other heart ratethresholds described herein, a number of methods may be used. One methodincludes determining a median of the most recent “m” RRIs and comparingthe median to a threshold heart rate. Another method requires a specificnumber “n” RRIs out of the most recent “m” RRIs to be shorter than aninterval corresponding to the threshold HR.

In one embodiment, a predetermined number “m” of consecutive RRIs arecollected and the nth smallest RRI out of the “m” intervals is used asan estimate of the current HR for comparison to a HR threshold. Forexample, the ninth smallest RRI out of the most recent 12 RRIs may beused as an estimate of the current HR for comparisons to HR thresholds.At block 157, if the ninth smallest RRI is shorter than a sudden changelimit interval, the detection algorithm proceeds to decision block 168.

The method of using the nth smallest RRI out a predetermined number ofcollected RRIs as a metric of HR can yield a different result than usinga median RRI. When using a median value, an undersensed event corruptsone RRI (by creating one very long RRI). An oversensed event corruptstwo RRIs (by creating two very short RRIs). Therefore, oversensing canresult in a corrupted median value more quickly than undersensing. Inpractice, oversensing is typically a more common occurrence thanundersensing in modern ICDs. Oversensing can result in an overestimateof the HR and could lead to unnecessary transitions to State 2. Byselecting the nth shortest RRI out of a specified number of recent,consecutive RRIs, the likelihood of transitioning to State 2 due tooversensing is reduced as compared to the method of using median RRIvalues as a metric of HR.

When the NF HR estimate exceeds the sudden change rate limit, acomparison of the NF HR to the FF HR at block 168 may be included toconfirm the detected NF HR. The comparison at block 168 may include adetermination relating to the reliability of the FF EGM signal to ensurethe FF signal is not noise or artifact corrupted and that the signalstrength is reliable. Either of the NF and FF signals may be deemedunreliable for estimating heart rate if a predetermined percentage ofsensed events have a peak amplitude at or near the minimum cardiac eventsensing threshold or above the event sensing threshold but below apredefined reliable threshold amplitude. A high frequency of sensedevents having amplitudes barely reaching the sensing threshold, or belowreliable amplitude threshold set slightly higher than the event sensingthreshold, may raise concern that these sensed events are oversensed orthat other events may be occurring that are undersensed. An EGM signalmay additionally or alternatively be determined to be unreliable if asensed event has not occurred for an undersensing threshold interval.For example, if at least 2 seconds or more have passed between twosensed events, the EGM signal may be classified as unreliable forestimating HR.

The combined NF and FF RRI measurements may be used in a variety of waysto verify an accurately sensed heart rate, without significant error dueto oversensing, undersensing, noise artifact or other factors. In oneembodiment, a NF HR may be verified using the FF HR at block 168 byverifying that for every sensed event on the NF EGM signal, there isalso a corresponding sensed event on the FF EGM signal occurring withina predefined interval of time from the NF sensed event, e.g. withinapproximately 20 ms.

A similar method for determining a metric of HR may be applied to the FFsignal as was applied to the NF signal, such as the foregoing example ofthe nth smallest RRI out of a most recent number of consecutive RRIs. Ifthe FF HR estimate does not approximately match the NF HR estimate, e.g.within a matching range, the detection algorithm remains in State 1. Inparticular, if the FF HR estimate is less than the sudden change limit,the lower HR estimate based on the FF HR is relied upon instead of theNF HR estimate. The process returns to block 152 to sense the next FFand NF events and measure the next RRI on both the FF and NF EGMsignals. While not shown explicitly in FIG. 4, if the FF HR estimate issignificantly different but faster than the NF HR rather than slower,e.g. faster than the SVT limit, a transition to State 2 at block 170 maybe made.

If the HR estimate from the FF EGM differs significantly from the heartrate estimate of the NF EGM, buffered RRIs used in making thisdetermination and/or FF and NF EGM signal segments may be stored asdiagnostic data at block 169 to record this occurrence of a mismatchbetween FF and NF HRs. Such diagnostics would be helpful for cliniciansand technicians to determine when and why the dual vector EGM signaldata is contradictory in terms of HR estimates and take correctiveaction as needed, e.g., when the contradictory results appear to be dueto noise, undersensing, lead-related conditions, or othernon-physiological causes.

As long as the HR remains below the sudden change limit (negative resultat block 158), either a sudden HR change detector 160 or a sudden RRIvariability change detector 164 will operate within State 1. At block159, the IMD controller determines if the detection algorithm isoperating in a low variability (LV) mode or a high variability (HV) modeas long as the NF HR remains below the sudden change rate limit. Controlof switching between a LV mode and a HV mode at block 159 will bedescribed in conjunction with FIG. 7.

In the LV mode, a HR change detector operates at block 160 for detectinga sudden change in HR based on sudden change detection criteria appliedat decision block 162. Details regarding the operation of the sudden HRchange detector at block 160 will be described in conjunction with FIG.5 below.

If sudden HR change criteria are met at block 162, and the NF HR isgreater than the detection lower limit (block 167), and if the NF and FFHRs approximately match (block 168), a transition to State 2 occurs atblock 170. The detection lower limit applied at block 167 is the limitapplied to the HR below which the heart rhythm is not a concerningrhythm even if a sudden change in HR or in RRI variability is detected.For example, the detection lower limit may nominally be set to 150 bpm.If the HR is less than the detection lower limit, at block 167, thedetection algorithm remains in State 1 and returns to block 156 toadvance to the next sensed event. The detection algorithm does notadvance to State 2 unless the HR estimate obtained on the current beatat least meets the detection lower limit requirement.

If the detection algorithm is operating in the HV mode (a negativeresult at block 159), a RRI variability change detector operates atblock 164. If the HR is highly variable from beat-to-beat, e.g. duringatrial fibrillation (AF), frequent ectopy, unstable intrinsicactivations, bigemeny, trigemeny, or other highly variable rhythms, asudden change in HR marking the onset of VT may be masked by the highlyvariable RRIs.

As such, when the RRIs are highly variable beat-to-beat, the tachycardiadiscrimination algorithm operates in a HV mode during State 1 to enabledetection of a sudden change in the RRI variability. Generally, if a VTarises from a rhythm characterized by highly variable RRIs, a suddendecrease in the RRI variability will occur. When criteria for detectinga sudden change in RRI variability are satisfied (block 166), the NF HRis greater than the detection lower limit (block 167), and the NF and FFHRs approximately match (block 168), a transition to State 2 occurs atblock 170. Details regarding the operation of the sudden RRI variabilitychange detector at block 164 will be described in conjunction with FIG.8 below.

FIG. 5 is a flow chart 200 of a sudden HR change detector that operatesduring the LV mode of State 1. The sudden HR change detector can operatein a reset mode 202 or a normal mode 210. The reset mode 202 operatesupon device initialization or in response to a manual reset of thealgorithm. During the reset mode 202, two metrics of RRIs from the NFEGM signal are initialized at block 204. A mean RRI (RRMEAN) isinitialized to a nominal value, for example 900 ms. Additionally, anexpected absolute difference between the next RRI and RRMEAN isinitialized. This expected absolute difference, referred to as RRMAD,defines a range around RRMEAN within which the next RRI is expected orpredicted to fall. A nominal initial value of RRMAD may be approximately800 ms.

The next “n” RRIs are used to update RRMEAN and RRMAD to actual valuesbased on actually measured RRIs. RRMEAN may be computed upon each newRRI as a weighted sum of the previous RRMEAN and the current RRI. Forexample, RRMEAN(updated)=0.5(RRMEAN)+0.5(RRI_(current)). While equalweighting coefficients are used in the foregoing equation, it isrecognized that other weighting coefficients may be used to rapidlyapproach an expected RRMEAN value during the reset mode 202.

RRMAD is updated with each new RRI as a weighted sum of the currentvalue of RRMAD and the difference between the currently measured RRI andcurrent value of RRMEAN. For example, RRMAD may be updated according tothe following equation:RRMAD(updated)=0.5(RRMAD)+0.5(|RRI_(current)−RRMEAN|+k*RRMEAN)

The “k*RRMEAN” term places a constraint on the minimum size of RRMADwherein ‘k’ is a small fixed value or percentage, e.g. less thanapproximately 0.05. Alternatively, RRMAD may be constrained by a fixedminimum value.

The number of RRIs, “n”, used for adapting RRMEAN and RRMAD during resetmode 202 may be in the range of approximately 3 to 8, without limitationIn one embodiment, the first five RRIs are used at block 206 to computeRRMEAN and RRMAD for defining an expected RRI range. If a current RRIdoes not fall within RRMEAN±RRMAD, that RRI is not used to update RRMEANor RRMAD and is not counted as one of the “n” RRIs for adapting RRMEANand RRMAD during the reset mode 202. After rapidly adapting RRMEAN andRRMAD from initial nominal values to actual expected values using thefirst “n” RRIs, the algorithm enters normal operation 210.

During normal operation 210, the expected RRI range is computed usingthe RRMEAN and RRMAD values at block 212:RRI(expected)=RRMEAN±RRMAD

When the next NF event is sensed (block 214), the RRI is measured andcompared to the expected RRI range at block 216. If the RRI is withinthe expected range, it is used to update RRMEAN and RRMAD at block 217.The formulas used to update RRMEAN and RRMAD at block 217 may bedifferent than the formulas used during the reset mode of operation 202.For example, different weighting coefficients may be used and/oradditional terms may be included. In one embodiment, RRMEAN is computedusing a relatively lower weighting applied to the current RRI, such as:RRMEAN(updated)=0.9(RRMEAN)+0.1(RRI_(current))

RRMAD may be computed as:RRMAD(updated)=0.95(RRMAD)+0.05*(d)*(|RRI_(current)−RRMEAN|+k*RRMEAN)*{1−((750−RRMEAN)/1000)}

wherein the constant “d” is a selected factor to stabilize the expectedrange, the term “k*RRMEAN” is included to constrain the minimum size ofRRMAD, and the factor {1−((750−RRMEAN)/1000)} forces the expected rangeto tighten as the HR increases and to expand as the HR decreases. Inother words, the expected RRI range narrows at higher HRs and widens atlower HRs. A maximum size of RRMAD may be defined to constrain themaximum expected range. In one embodiment, RRMAD is limited to a maximumpercentage of RRMEAN, for example approximately 20% of RRMEAN.

If an RRI is outside the expected range (RRMEAN±RRMAD), it is not usedto compute updated values of RRMEAN and RRMAD. A lost counter is updatedat block 220 to count the number of RRIs that are not used for updatingthe expected range metrics. If the current RRI is greater thanRRMEAN+RRMAD, the lost counter is increased by one. If the current RRIis less than RRMEAN−RRMAD, the lost counter is decreased by one.

The lost counter may have a value ranging between the positive andnegative values of a lost threshold. When the RRI falls within theexpected range (block 216) and is used to update RRMEAN and RRMAD (block217), the lost counter is updated at block 218 by moving its value onestep closer to zero from whatever its current value is.

When the lost counter is increased or decreased in response to an out ofrange RRI (block 220), the lost counter is compared to a lost thresholdat block 222. If the lost threshold has been reached before changing toState 2, the expected RRI range is declared lost at block 224. Theexpected RRI range is updated at block 226 by adjusting the value ofRRMEAN up or down by a percentage of RRMAD, depending on the value ofthe lost counter.

In one embodiment, if the current RRI is greater than the expected rangeand the positive lost threshold is reached, RRMEAN is increased by 25%of RRMAD at block 226 to update the expected RRI range. If the currentRRI is less than the expected range and the negative lost threshold isreached, RRMEAN is decreased by 25% of RRMAD at block 226. In this way,a shift in RRMEAN (or multiple shifts in RRMEAN as required) repositionsthe expected RRI range so that the repositioned range again representsthe range of currently expected RRIs. This repositioning of the expectedRRI range can occur when the HR remains less than the sudden changelimit and other sudden change detection criteria for transitioning toState 2 have not been met. The algorithm remains in State 1 and returnsto block 214 to sense the next NF event.

If the lost threshold has not been met at block 222, an Out of RangeCounter is updated at block 228. If the RRI is unexpectedly short, i.e.less than RRMEAN−RRMAD, the Out of Range Counter is increased by one.Otherwise, if the RRI is within or greater than the expected range, theOut of Range Counter is decreased by two. The Out of Range counter isused to count the number of RRIs that are consistently shorter than theexpected RRI range. If the count trends upward, consistently short RRIsare occurring indicating the possibility of a sudden change in HR. TheOut of Range counter has a minimum limit of zero and a maximum limit,e.g. 20.

The Out of Range Counter is compared to a threshold count for detectinga sudden change in HR at block 230. If the sudden change detectionthreshold has not been reached, and the algorithm is still operating inthe LV mode (as determined at block 232), the algorithm remains in State1 and the process returns to block 212. The expected RRI range in thiscase will remain the same since the current RRI is out of range and willnot be used to compute new RRMEAN and RRMAD values.

If the Out of Range Counter exceeds the sudden change detectionthreshold at block 230, e.g. a threshold of 10, indicating recent RRIsare consistently shorter than an expected range, the NF HR is comparedto the detection lower limit at block 234. As described previously, a NFHR may be estimated as the nth smallest RRI out of a specified number ofthe most recent RRIs. If the NF HR estimate does not exceed a detectionlower rate limit for detecting tachycardia, and the algorithm is stillin the LV mode (block 232), the process returns to block 212. Theexpected RRI range will again remain the same because the current RRI isout of range. Even though a sudden HR change has been detected, the HRis too low to be considered a concerning heart rhythm for tachycardiadetection purposes.

If the NF HR is faster than the detection lower limit as determined atblock 234, the HR from the FF EGM signal is checked to verify the NF HR.At block 236, the FF EGM signal is first analyzed to determine if thesignal is reliable. Since the FF EGM signal is more susceptible to noiseor artifact, noise/artifact rejection criteria may be applied to the FFEGM signal to reject the FF HR data when it is determined to beunreliable. The FF EGM must also be of sufficient amplitude in order tobe considered “reliable”. In other words, if the FF R-wave signals areof very small amplitude, the HR estimate that comes from the FF EGM isconsidered unreliable and is not used to verify or disprove a NF HR.

Specific criteria relating to EGM signal amplitude and/or FF RRIs may beapplied to the FF signal at block 236 to verify that it is a reliablesignal for estimating the HR. For example, the FF EGM signal may bedetermined unreliable if an unacceptable number of R-waves out of apredetermined number of the most recent R-waves (sensed on the FF EGMsignal) are less than a threshold amplitude and/or extremely short orextremely long RRIs are present. In one specific example, the FF EGM isdetermined to be an unreliable signal if the third shortest RRI out ofthe most recent 12 RRIs is less than 500 ms and at least 4 of the mostrecent 12 sensed R-waves have peak amplitudes less than 500 microvoltswith at least one of those low amplitude R-waves being within the mostrecent three sensed R-waves. Additionally, the FF EGM signal can bedetermined unreliable if a sensed event has not occurred within somemaximum time limit (indicating a low amplitude signal and possibleundersensing). For example, if at least approximately 2,500 ms havepassed since the most recent FF sensed event the FF EGM signal isdetermined to be unreliable.

If the FF EGM signal is determined to be unreliable, a FF unreliablecounter is increased at block 238. The NF EGM signal evidence for aconcerning rhythm is then relied upon for transitioning to State 2, the“concerned” state, at block 244. The FF EGM is not used to either verifyor disprove the NF EGM result in detecting a concerning rhythm.

In one embodiment, if the unreliable signal criteria are met at block236, the FF signal remains classified as unreliable for a period oftime. To accomplish this, the FF unreliable counter is set to a maximumvalue, e.g. 12, at block 238 when the unreliable criteria are met. TheFF HR estimate is set to the same value as the NF HR estimate at block239. As a result, the NF and FF heart rates will certainly match atdecision block 243, and a transition to State 2 occurs at bock 244.

When the FF EGM signal is found to be reliable at block 236, the FFunreliable counter is decreased by one at block 240. As long as the FFunreliable counter remains greater than zero, as determined at block242, the FF EGM signal is considered unreliable. The FF HR estimate isset equal to the NF HR estimate at block 239, resulting in an automaticmatch of the NF and FF HRs at block 243, and a transition to State 2 atblock 244.

While not explicitly shown in the flow charts provided, a similaranalysis of the NF EGM signal may be performed to determine when the NFsignal is unreliable. If the NF EGM signal is found to be unreliable,the FF EGM signal may be used as the primary sensing signal for sensingcardiac events and setting a morphology analysis window until the NF EGMsignal is found to be reliable again.

If the FF unreliable counter has reached zero at block 242, the FF HR isestimated and compared to the NF HR at block 243. The FF HR may beestimated using a similar method as described above for estimating theNF HR (i.e. the nth RRI out of “m” most recent RRIs). When the FF HRestimate approximately matches the NF HR estimate (block 243), or whenthe FF HR estimate exceeds the sudden change limit, the determination ofa concerning rhythm is confirmed by the FF signal. Transition to state 2occurs at block 244. A HR match may be defined as a NF HR estimate andFF HR estimate being with a predefined range or percentage of eachother.

On the other hand, if the FF EGM signal is reliable, the FF HR estimatedoes not approximately match the NF HR estimate, and is not greater thanthe sudden change limit at block 243, the transition to State 2 does notoccur. The algorithm returns to block 232.

At block 232, if a switch from the LV mode to the HV mode has occurred,the method for detecting a sudden change in the heart rhythm switchesfrom the sudden HR change detector to a sudden RRI variability detectorat block 242. Otherwise the detection algorithm remains in the LV modeand returns to block 212. The expected RRI range will remain the samefor the current beat and the process will advance to the next NF sensedevent at block 214.

FIG. 6 is a plot of the expected RRI range computed using the RRMEAN andRRMAD metrics of RRIs as described above. Measured RRIs are representedby open circles and are plotted in ms along the y-axis over time inseconds along the x-axis. RRMEAN 182 is computed from the measured RRIsand is shown by a solid line. The positive boundary 184 a and negativeboundary 184 b, collectively 184, are defined by ±RRMAD and are shown bythe dashed lines above and below RRMEAN 182. The boundaries 184 a and184 b define the RRI range in which the next RRI is predicted to fallbased on past RRIs.

An initial value 186 of 900 ms is assigned to RRMEAN, and an initialvalue of 800 ms is assigned to RRMAD. During a reset mode of operation188, the first five RRIs are used to rapidly converge on an actualRRMEAN value and an actual RRMAD value using the equations providedabove. Normal operation 190 a of State 1 of the detection algorithmbegins after the reset mode 188. Initially, a string of consistent 1000ms RRIs 191 occurs. RRMEAN 182 tracks the consistent RRIs. The ±RRMADupper and lower boundaries 184 gradually tighten around RRMEAN to narrowthe expected RRI range.

An interval of variable RRIs 192 causes the expected RRI range to expandas can be seen by a widening of the ±RRMAD boundaries 184. Following thevariable RRIs 192, a series of high rate RRIs 193 occurs. These RRIs aresuddenly shortened but remain longer than a nominal detection lowerlimit interval of 500 ms such that a state transition does not occur.When the sudden rate change occurs, the short RRIs are out of theexpected RRI range. The RRMEAN and RRMAD metrics are not adjusted inresponse to the out-of-range RRIs and exhibit a flat response to theconsistently out of range RRIs.

After ten RRIs that are consistently out of range, the lost counterreaches a threshold count for repositioning the expected RRI range. Alost mode 194 operates for repositioning the expected RRI range. In thisexample, the RRIs are consistently less than the expected range, but theHR is still lower than a detection lower rate limit so the algorithmremains in State 2. When current RRI is less than the expected RRIrange, the expected RRI range is repositioned by adjusting RRMEAN by apredetermined decrement on a beat-by-beat basis until the current RRIfalls within the expected range.

If RRIs are consistently greater than an expected RRI range, RRMEANwould be increased by a predetermined increment on each RRI toreposition the expected RRI range. In one embodiment, when a lost countthreshold is reached, RRMEAN is decreased or increased as needed by apercentage of the current value of RRMAD, for example 25% of RRMAD. Thisadjustment of RRMEAN allows the expected RRI range to be quicklyrepositioned to include a current RRI. Thereafter, normal operation 190b resumes.

RRMEAN and RRMAD are updated according to the normal operation equationsas each RRI falls within the expected range during normal operation 190b. At 195, the RRIs increase to 900 ms, which is still within theexpected RRI range as defined by the ±RRMAD boundaries 184. RRMEAN andRRMAD continue to be adjusted on a beat-by-beat basis using theequations described above. A gradual tightening of the expected RRIrange is observed.

FIG. 7 is a flow chart 250 of a method for controlling switching betweenLV and HV modes of operation during State 1. As described previously,during the LV mode, a sudden HR change detector operates. During the HVmode, a sudden RRI variability change detector operates. In order tocontrol which of the LV and HV modes the detection algorithm isoperating in, a metric of the variability of the RRIs, “MEANVAR”, ismonitored.

In flow chart 250, reset operation 202 and normal operation 210correspond to the reset operation and normal operation shown in FIG. 5.Thus, processes shown in FIG. 7 that occur during reset operation 202and during normal operation 210 are in addition to the processesdescribed during reset and normal operation in conjunction with FIG. 5.

During reset operation 202, in addition to computing initial values forRRMEAN and RRMAD, an initial value for MEANVAR is computed for the first“n” RRIs measured on the NF EGM signal. MEANVAR is computed as aweighted sum of the current value of MEANVAR and the difference betweenthe current RRI and the previous RRI. For example:MEANVAR(updated)=W ₁(MEANVAR)+W ₂(|RRI_(i)−RRI_(i-1)|)

During the reset mode, MEANVAR may be assigned an initial nominal valuethen updated to an actual MEANVAR using the above equations. Duringreset, W₁ and W₂ may be set to equal values of 0.5.

During normal operation 210, the NF EGM signal is acquired at block 260for sensing the next NF event. During normal operation, MEANVAR may becomputed using a weighted sum of the current MEANVAR value and thedifference between the current RRI and previous RRI. In one embodiment,the current MEANVAR may be multiplied by a weighting coefficient W1 ofapproximately 0.9 or higher and the current RRI difference may bemultiplied by a weighting coefficient W2 of approximately 0.1 or lower.For example W1 may be approximately 0.96 and W2 may be approximately0.04.

A maximum upper limit may be applied to MEANVAR, which may be defined asa percentage of RRMEAN, for example approximately 25% of RRMEAN. Inorder to limit the influence of outliers, a limit may also be applied tothe current RRI difference used to compute MEANVAR. For example, if thecurrent RRI difference is greater than the current value of MEANVAR, thecurrent RRI difference is replaced by the sum of MEANVAR and the largerof MEANVAR and 20 ms.

MEANVAR is updated in response to the NF event at block 262. If theMEANVAR is greater than a first HV threshold, as determined at block264, the detection algorithm is switched to the HV mode at block 266.Operations for detecting a sudden change during the HV mode will bedescribed in conjunction with FIG. 8.

Upon entering the HV mode, a reference HR estimate, OLD RRI AVG, iscomputed at block 267. The OLD RRI AVG may be computed as the mean ofthe most recent RRIs, for example 12 to 16 of the most recent RRIs, andis a measure of the heart rate upon entering the HV mode. As will bedescribed in greater detail below, the OLD RRI AVG is used for detectingan increasing trend in HR in the presence of a decrease in RRIvariability. This combination of a sudden decrease in RRI variabilityaccompanied by an increasing trend in HR is an indication of aconcerning heart rhythm and can trigger a state transition of thedetection algorithm as described below. The increasing trend in HRaccompanying a sudden change in RRI variability does not necessarilyneed to meet criteria for detecting a “sudden” increase in HR, asrequired by the sudden HR change detector during the LV mode. In the HVmode, a more gradual increase in HR, in conjunction with a suddendecrease in RRI variability, may satisfy criteria for detecting a“sudden change” in the heart rhythm.

During the HV mode, the next NF event is sensed at block 268 and used toupdate MEANVAR at block 270. If MEANVAR falls below a second LVthreshold, as determined at block 272, the detection algorithm switchesto the LV mode at block 274. The first HV threshold, THRESHOLD1, used atdecision block 264 for switching from a LV mode to a HV mode can bedefined as a percentage of RRMEAN or a fixed value. In one embodiment,THRESHOLD1 is set to be in the range of approximately fifteen to twentypercent of RRMEAN. Additionally, a fixed maximum upper limit of MEANVARduring the LV mode may be defined, above which a switch to HV modeoccurs. For example, if MEANVAR is greater than approximately0.18*RRMEAN or greater than a fixed upper limit of 100 ms, the detectionalgorithm switches to HV mode.

The second LV threshold used at decision block 272 for switching back tothe LV mode may be defined the same or differently than the firstthreshold. In one embodiment, the THRESHOLD2 applied to MEANVAR forswitching back to the LV mode is set lower than the first threshold usedfor switching to the HV mode. For example, the threshold for switchingback to LV mode may be defined to be between approximately ten andfifteen percent of RRMEAN. Additionally, a fixed lower limit of MEANVARduring the HV mode may be defined, below which a switch to LV modeoccurs. In one embodiment, the detection algorithm switches from the HVmode to the LV mode if MEANVAR is less than 0.12*RRMEAN or less than alower limit of approximately 70 ms. The hysteresis between switchinginto and out of the HV mode can reduce switching frequency. The upperand lower limits applied to MEANVAR allow switching to occur when thevariability becomes very low or very high independent of the currentvalue of RRMEAN.

After switching to the LV mode at block 274, a LV counter is compared tohalf of the sudden change detection threshold, also referred to hereinas “sudden change threshold”. As will be described in conjunction withFIG. 8, the LV counter is used to count the number of RRIs having a lowbeat-to-beat variability during the HV mode of operation. When the LVcounter exceeds a sudden change threshold during the HV mode, a suddenchange in RRI variability may be detected. The sudden change thresholdapplied to the LV count (during HV mode) and the sudden change thresholdapplied to the RRI out of range count (during LV mode) may be equal orset to distinct values during the different HV and LV operating modes.

The MEANVAR metric of RRI variability is used differently than the LVcounter. The MEANVAR metric is used to control switching between the HVmode and the LV mode within State 1 while the LV counter is used todetect a sudden decrease in RRI variability and cause transition fromState 1 to State 2 during the HV mode.

If the MEANVAR has decreased to cause a switch from the HV mode to theLV mode at block 274, the current value of the LV counter upon switchingfrom the HV mode is compared to a percentage of the sudden changedetection threshold at block 276, for example half of the sudden changedetection threshold. If the current value of the LV counter is notgreater than the selected percentage of the sudden change detectionthreshold, the LV mode of operation proceeds as described above inconjunction with FIG. 5. However, if the LV counter is moderately high(e.g. meeting at least half the sudden change detection threshold), aNEW RRI AVG is computed at block 278 to determine if this decrease inRRI variability is also accompanied by an increase in HR. The NEW RRIAVG may be computed as the mean of a predetermined number of the mostrecent RRIs. For example the most recent eight RRIs (or another number)occurring consecutively up to and including the RRI which caused aswitch to the LV mode may be used to compute the NEW RRI AVG.

At block 280, this NEW RRI AVG is compared to the reference HR estimate,OLD RRI AVG computed at block 267 upon entering the HV mode, todetermine if the transition out of the HV mode to the LV mode is alsoaccompanied by an increasing trend in HR. A ratio of or differencebetween the NEW RRI AVG and the OLD RRI AVG may be compared to athreshold for detecting evidence of an increasing HR at block 280. Forexample if the NEW RRI AVG is less than approximately eighty percent (oranother percentage) of the OLD RRI AVG, an increasing HR is detected.

If the change to the LV mode occurs with a LV count greater than halfthe sudden change detection threshold but is not accompanied by anincreasing HR (block 280), the detection algorithm proceeds to operatenormally in the LV mode (return to block 260). If an increase in HR isdetected, however, this increase in combination with transition to a LVmode with a moderately high LV count may be an indication of a suddenchange in the heart rhythm warranting a change to the concerned State 2.

To meet state transition criteria, the Out of Range counter is set to asuprathreshold value for detecting a sudden change at block 284. Forexample, if the threshold count for detecting a sudden change is set to10, the Out Range counter may be set to 16 at block 284. This highcounter value immediately satisfies the state transition requirementapplied to the Out of Range counter during the LV mode. Setting the Outof Range counter to a high value allows time for the FF EGM signal to beanalyzed to verify a match between the FF and NF HR estimates, which maybe an added requirement before transitioning to State 2.

A FF HR estimate is computed and compared to a NF HR estimate at block288. The process performed at block 288 may correspond generally toblocks 236 through 243 of FIG. 5 wherein the FF EGM signal reliabilityis first determined and if found reliable a FF HR estimate isdetermined. If the NF and FF HR estimates match, or the FF HR estimateis greater than the sudden change limit, a transition to State 2 occursat block 290. If the FF EGM signal is unreliable, the results of the NFsignal analysis are relied on for effecting a state transition at block290. Otherwise, when the FF signal is found reliable, but the FF HR doesnot match the NF heart rate estimate, the transition to State 2 does notoccur. The process returns to block 210 and remains in the LV mode ofState 1.

FIG. 8 is a flow chart 300 of operations performed by the sudden RRIvariability change detector during the HV mode. Upon switching from theLV mode to the HV mode at block 302, the detection algorithm resets a LVcounter to zero at block 304. The LV counter is used to count RRIdifferences that are smaller than expected during the HV mode ofoperation. A high count of less than expected RRI differences indicatesconsistently low RRI variability. A change in the heart rhythm fromhighly variable RRIs to small beat-to-beat RRI variation may beassociated with VT and may therefore be identified as a concerningrhythm, particularly when accompanied by an increase in HR.

A metric of the average HR, OLD RRI AVG is computed (block 305), uponentering the HV mode. This metric OLD RRI AVG is used as a reference HRfor determining if an increase in HR accompanies a decrease in RRIvariability. The combination of a sudden change from high to low RRIvariability and increased HR is used to detect a sudden change in theheart rhythm during the HV mode of operation in State 1. The OLD RRI AVGmay be computed as the average of the most recent RRIs, for example themost recent sixteen consecutive RRIs.

At block 306, the next NF event is sensed and used to update MEANVAR atblock 308. As described in conjunction with FIG. 7, MEANVAR is used totrack RRI variability for controlling switching between the HV and LVmodes and was initialized during the reset operation 202 shown in FIG.7. MEANVAR is also used in conjunction with a LV counter for detecting asudden change in RRI variability during the HV mode.

At block 310, the absolute difference between the current RRI and theprevious RRI, i.e. the current RRI difference, is compared to a lowvariability threshold. The low variability threshold applied to the RRIdifferences may be defined as a percentage of MEANVAR such that thecurrent RRI variability is compared to an expected variability metric.In one embodiment, the low variability threshold applied to thebeat-to-beat RRI differences is 0.5*MEANVAR. The low variabilitythreshold may include an absolute limit of the beat-to-beat variability.For example, if the current RRI difference is less than 0.5*MEANVAR orless than approximately 30 ms, the current RRI difference may beconsidered to be low.

If the difference is less than the low variability threshold (evidenceof low RRI variability), the current value of MEANVAR is compared to aminimum MEANVAR threshold at block 318. If the current MEANVAR isgreater than the minimum threshold, the LV counter is increased at block320. The requirement that MEANVAR be greater than a minimum threshold isincluded such that the detection of a significant decrease in RRIvariability can occur only when the mean variability is already greaterthan some minimum level to begin with. If the MEANVAR is above a minimumlevel, the current RRI difference less than a LV threshold represents apotentially sudden decrease in RRI variability. The LV counter isincreased at block 320 to maintain a count of the RRI differences thatare less than the LV threshold (block 310) when MEANVAR is above theminimum threshold (block 318). RRI differences meeting these criteriaprovide evidence of a sudden change from high RRI variability to low RRIvariability.

If the current RRI difference is low (i.e. less than the LV threshold atblock 310), and MEANVAR is also less than a minimum threshold, e.g. lessthan approximately 20 ms, the LV counter may be decreased at block 319.MEANVAR computed as a running mean of RRI variability is not high enoughto detect a decrease in RRI variability. The detection algorithm remainsin the HV mode in State 1, and returns to block 306 to sense the next NFevent.

When the LV counter is increased at block 320, it is compared to asudden change threshold at block 322. If the LV count is greater thanthe sudden change threshold, a NEW RRI AVG is computed at block 323 as ametric of the current HR. The NEW RRI AVG may be computed as an averageof the most recent RRIs, for example the most recent eight RRIsoccurring consecutively up to and including the RRI which caused the LVcounter to exceed the sudden change threshold.

The NEW RRI AVG is compared to the reference OLD RRI AVG to determine ifthe sudden change in RRI variability is accompanied by an increasingtrend in HR. In one embodiment, a ratio of or difference between the NEWRRI AVG and the OLD RRI AVG is compared to a threshold. For example ifthe NEW RRI AVG is less than approximately ninety percent of the OLD RRIAVG, evidence of an increasing HR is detected at block 324. It isrecognized that other methods of estimating a current HR and a referenceHR and alternative threshold criteria can be used for detecting evidenceof an increasing HR associated with a sudden change in RRI variability.

If evidence of an increasing HR accompanying the sudden change in RRIvariability is detected at block 324, a sudden change in the heartrhythm is detected at block 325. A transition from the unconcerned State1 to the concerned State 2 occurs at block 326. If the LV counter hasnot reached the sudden change threshold (block 322) or the HR has notincreased to meet criteria for detecting an increase in HR (block 324),the algorithm returns to block 306 to sense the next NF event.

Referring again to block 310, if the difference between the current RRIand previous RRI is greater than the low variability threshold (evidenceof sustained high RRI variability), the RRI difference is compared to amaximum variability threshold at block 312. If the RRI difference isgreater than a maximum variability threshold, e.g. greater thanapproximately 90 ms, then the LV counter is reset to zero at block 314.The detection algorithm remains in the HV mode of operation in State 1and returns to block 305 to compute an updated value of OLD RRI AVG.

In some embodiments, OLD RRI AVG is updated every time the LV counter isreset to zero. In other embodiments, additional criteria relating to thebehavior of RRI differences may be required before updating the OLD RRIAVG value at block 305. For example, a predetermined number ofconsecutive RRI differences greater than the maximum variabilitythreshold may be required before updating the OLD RRI AVG value. Anothercriterion that may be required before updating OLD RRI AVG is thatMEANVAR is greater than the MEANVAR minimum.

In one embodiment, OLD RRI AVG is computed when the LV counter is resetto zero and at least four consecutive RRI differences have exceeded themaximum variability threshold (e.g. 90 ms). Alternatively, OLD RRI AVGis updated when the consecutive RRI differences at least meet anotherlower threshold (e.g. 30 ms or a percentage of MEANVAR) and MEANVAR isat least greater than the MEANVAR minimum value (e.g. 20 ms). Variouscriteria regarding the current LV counter value, behavior of the mostrecent RRI differences and/or MEANVAR may be used alone or incombination for determining when to compute an updated value of OLD RRIAVG.

When updating OLD RRI AVG, the formula for computing OLD RRI AVG may bethe same or different than the formula used to compute an initial valueof OLD RRI AVG upon entering the HV mode. For example, in both cases themost recent sixteen (or another number) RRIs may be averaged to computeOLD RRI AVG. In other embodiments, a different number of recent RRIs maybe used when OLD RRI AVG is updated in response to resetting the LVcounter during the HV mode of operation as compared to the number ofRRIs used to compute OLD RRI AVG upon entering the HV mode.

If the current RRI difference at block 310 is greater than the lowvariability threshold but not greater than the maximum variabilitythreshold (negative result at block 312), the LV counter is decreased atblock 316. In summary, in response to moderate beat-to-beat variability,the LV counter is decreased (block 316). In response to highvariability, the LV counter is reset to zero (block 314). In response tolow variability, the LV counter is increased (block 320) as long as thecurrent MEANVAR is greater than a predetermined minimum value. The LVcounter will reach a sudden change threshold when the RRI differencesare consistently small. This low variability in RRIs following a periodof high variability (MEANVAR greater than a minimum threshold) and anaccompanying increase in HR is evidence of a concerning rhythm resultingin transition to State 2.

In summary, a transition from the unconcerned State 1 to the concernedState 2 may occur in response to at least four conditions. One conditionthat causes a transition to State 2 is the detection of a suddenincrease in HR during the LV mode of operation as described inconjunction with FIG. 5. Another condition that causes a State 1 toState 2 transition is the detection of a sudden decrease in RRIvariability accompanied by an increasing HR during the HV mode ofoperation as described in conjunction with FIG. 8. Still anothercondition that causes a transition to State 2 is a moderate decrease inRRI variability that results in a switch from the HV mode to the LV modewithin State 1 accompanied by evidence of increasing HR as described inconjunction with FIG. 7. These conditions each relate to the detectionof a sudden change in the rhythm when the estimated HR is less than asudden change rate limit but greater than a detection lower rate limit.When the estimated HR is greater than the sudden change rate limit, atransition from State 1 to State 2 occurs independent of the sudden HRchange detector and the sudden RRI variability change detector (as seenat step 157 of FIG. 4). The high HR alone is cause for a concerningrhythm.

Any of the situations relating to a sudden change in HR, a sudden changein RRI variability, or a combination of decreasing RRI variability andincreasing HR, when detected consistently enough from beat-to-beat tocause the various counters described herein to reach a predefined suddenchange detection threshold level, are inclusively referred to herein asa “sudden change” in the heart rhythm. A sudden change warrantsadditional State 2 monitoring of the EGM signal for detecting anddiscriminating tachycardia. Thus various criteria can be definedrelating to a sudden increase in HR, a sudden decrease in RRIvariability, or a combination of consistently increasing HR anddecreasing RRI variability, for use in effecting a transition from State1 to State 2.

FIG. 9 is a flow chart 350 of one method for comparing a NF HR and a FFHR for verifying a NF HR estimate when other sudden change detectioncriteria are met for transitioning from State 1 to State 2. The processshown in flow chart 350 may correspond to block 168 of FIG. 4, block 243of FIG. 5, or block 288 in FIG. 7.

At block 351, a counter used for detecting a sudden change during State1 is increased. The counter may be the Out of Range counter used tocount RRIs falling outside an expected RRI range (LV mode) or the LVcounter used to count RRI differences that are less than a LV threshold(HV mode). If a sudden change counter is increased, the current NF RRIwhich resulted in the increase is buffered at block 352. NF RRIs thatcontribute to a sudden change detection are buffered for use indetermining a metric of the NF HR.

The method used to compute the metric of the NF HR from the buffered NFRRIs depends on the change detection threshold applied to the Out ofRange counter or LV counter. If the sudden change detection threshold isX, X−1 buffered RRIs are used at block 356 to compute a NF HR estimate.The value X may be nominally 10 but may range, for example, between 6and 16.

The NF HR estimate is referred to as the NF RR change interval in flowchart 350 and is measured as the average of two out of the X−1 bufferedRRIs. For example, if the change detection threshold is set to 10, thesixth and seventh smallest RRIs out of the most recent 9 buffered RRIsmay be averaged to compute the NF RR change interval.

If the sudden change threshold is met at block 361 (either the Out ofRange counter or the LV counter reaches or exceeds the sudden changethreshold), the FF EGM signal is used to verify the NF HR estimatecomputed as the NF RR change interval. As described previously, if theFF EGM signal is unreliable, as determined at block 362, the FF signalis not used to verify the NF HR estimate. A transition to State 2 mayoccur in response to the NF HR estimate and the sudden change detection.

If the FF EGM signal is reliable (block 362), the FF RR change intervalis computed at block 363 as an estimate of HR. The FF RR change intervalmay be computed in a similar manner as the NF RR change interval, i.e.averaging selected RRIs out of the X−1 most recent FF RRIs. Theseintervals may be the X−1 most recent consecutive FF RRIs and notnecessarily be FF RRIs that correspond in time to the buffered NF RRIs.When buffering the NF RRIs that cause an increase in a change counter,intervening RRIs that do not cause an increase in the change counter arenot buffered and are not used for computing the NF RR change interval.As such, the NF RRIs used to compute the NF change interval may not bethe most recent consecutive X−1 intervals. In an alternative embodiment,each time a NF RRI is buffered, the corresponding FF RRI may be bufferedfor use in computing the FF RR change interval.

At block 364, the NF and FF change intervals are compared to determineif the NF and FF heart rate estimates approximately match. If the NF andFF change intervals are within a predetermined threshold, e.g.approximately 20 ms of each other, the FF and NF heart rate estimatesare determined to approximately match. The sudden change detectioncriteria are met, causing a transition to State 2 at block 370.

If the NF and FF change intervals do not approximately match at block364, the detection algorithm remains in State 1. The process shown inFIG. 9 returns to block 351 to wait for the next increase in a suddenchange counter.

FIG. 10 is a flow chart 400 providing an overview of operationsperformed during the concerned State 2. The tachycardia detectionalgorithm continues to use simultaneously acquired EGM signals sensedfrom two different sensing vectors at block 402. The two sensing vectorsare used for performing tachycardia detection operations, includingcomputing a tachycardia expected RRI range at block 403, rejectingnoise/artifact at block 404, performing an overall signal morphologyanalysis at block 405, and for extracting specific beat features atblock 407 for additional analysis when needed.

At block 403, a tachycardia expected range is computed from one of theEGM signals, e.g. the NF EGM signal. The tachycardia expected range isanalogous to the expected RRI range used in State 1. The tachycardiaexpected range, however, represents an RRI range expected from thecurrent, concerning rhythm, rather than in the preceding normal,unconcerning rhythm. Similar to the expected RRI range computed duringState 1, the tachycardia expected range computation at block 403 mayinclude computing RRMEAN and RRMAD values computed using a weighted sumof the current RRI and the previous RRMEAN and RRMAD values. The initialvalues of RRMEAN and RRMAD used to compute the tachycardia expectedrange may be set to nominal values, e.g. 500 ms, and quickly adjusted toactual values using the most recent five RRIs (or another number ofRRIs).

The last expected RRI range computed in State 1 before transitioning toState 2 is stored and will not be updated during State 2. The State 1expected RRI range is thus frozen during State 2 operations. Theexpected RRI range existing upon transition from State 1 to State 2represents an expected HR upon return to a normal rhythm. As such, theexpected RRI range value upon transitioning to State 2 is stored for usein controlling a transition back to State 1, as will be described indetail below.

At block 404, a noise/artifact rejection process is performed thatanalyzes each of the FF and NF EGM signals to determine the presence ofnoise or artifact that may corrupt the tachycardia discriminationalgorithm. Each heart beat will be given a noise/artifact classificationto exclude corrupted beats from contributing to the tachycardiadiscrimination methods. Various methods for detecting noise or artifactin the EGM signals may be used. One method for classifying a currentbeat as corrupted or non-corrupted is described below in conjunctionwith FIG. 18.

Each heart beat that is classified as a non-corrupted beat is analyzedmorphologically at blocks 405 and 407 as needed. The results of anoverall morphology analysis and specific beat feature analysiscontribute in a cumulative manner on a beat-by-beat basis to a VTevidence metric at block 406. As will be described in detail herein, aVT evidence counter is adjusted beat-by-beat according to specific rulesrelating to an overall morphology analysis of the FF EGM signal and/orthe NF EGM signal and/or specific beat features of the FF and/or NF EGMsignals.

In some rhythms, changes in specific beat features as compared to anormal sinus rhythm beat, on either the FF or NF EGM signals, may have ahigher tachycardia discrimination power than an overall morphologyassessment of the same signal alone. As such, specific beat features areused to enhance the sensitivity and specificity of the tachycardiadiscrimination method.

At block 408, the tachycardia expected range and a VT evidence counterare used in a VT detection process to detect VT and advance to convincedState 3, or to make a determination to return to the unconcernedState 1. An expected RRI range stored from State 1 operations may beused in making a decision to return to State 1. If the VT evidencecounter has reached a detection threshold, VT will be detected and atransition from the concerned State 2 to the convinced State 3 occurs.As will be described in detail below, criteria are defined to govern thetransition between State 2 and State 3 and from State 2 back to State 1.The criteria may include requirements applied to results of thenoise/artifact rejection analysis 404, VT evidence accumulation (block406), the tachycardia expected range (block 403) and a stored expectedRRI range from State 1.

FIG. 11 is a flow chart 410 of a method for discriminating between VT(treatable) and SVT (non-treatable) rhythms during State 2 operations.In general, when the estimated HR is greater than a tachycardiadetection lower rate limit but less than an SVT detection upper ratelimit, the current heart rhythm is classified as “non-treatable” unlessproven otherwise by the accumulation of VT evidence on a beat-by-beatbasis. At blocks 412 and 414, two different EGM sensing vectors areemployed for simultaneously recording two different EGM signals, e.g.the FF and NF EGM signals described above.

In one embodiment, a NF signal sensed at block 412 is used at block 416for sensing ventricular events, i.e. R-waves. Upon sensing a ventricularevent at block 416, an analysis window is set at block 418 defining aninterval for analyzing both the FF and NF EGM signal for the sensedheart beat. While the NF EGM signal may be used to set the analysiswindow based on NF sensed events, the analysis window may be applied toboth the NF signal and the FF signal for purposes of waveform morphologyanalysis and extracting specific beat features. In other embodiments,separate analysis windows may be set and applied to the EGM signalsbased on events sensed from the respective EGM signal.

At block 420, morphology analysis of the FF EGM signal within theanalysis window is performed. This analysis is referred to as an“overall” morphology analysis because the morphology of the entire EGMsignal within the analysis window is compared to the morphology of anEGM template obtained over a similar time window. In other words, aspecific amplitude, slope, or other time point within the analysiswindow is not isolated for analysis when performing the overallmorphology analysis. The morphology of the waveform as a whole duringthe analysis window is compared to a known template morphology as awhole to determine a degree of matching between the unknown beat and theknown template. The analysis window generally encompasses at least theQRS complex but may include more or less of the EGM signal depending onthe analysis window duration and accuracy of R-wave detection.

Numerous morphology analysis algorithms are available which may beapplied at block 420. In general, a morphology analysis is performed tocompare the overall morphology of a sensed EGM signal during theanalysis window of an unknown beat to the morphology of a known heartbeat for use in classifying the unknown beat. For example, in Waveletanalysis, the morphology of the FF EGM signal is compared to a knowntemplate for a normal sinus rhythm beat to determine if the R-wavesignal matches the normal sinus rhythm template. Reference is made toU.S. Pat. No. 6,393,316 (Gillberg et al.), incorporated herein byreference in its entirety.

A morphology matching score is computed at block 422 as a measure of howclosely the overall morphology of the sensed EGM signal of an unknownbeat matches the overall morphology of a known template of a normallyconducted beat. A high matching score generally indicates that theunknown sensed ventricular beat is a conducted beat arising from theatrial chambers. A low matching score generally indicates that thesensed ventricular beat is not a normally conducted beat and originatesin the ventricular chambers.

In past practice, VT detection algorithms compared a morphology score toa threshold and the sensed heart beat was classified accordingly. Forexample, in a Wavelet morphology analysis, a VT beat threshold may beset such that if the wavelet matching score falls below the threshold,the unknown beat is classified as a VT beat. If the matching scoreexceeds the threshold, the unknown beat is classified as an SVT beat. VTor SVT is detected based on this threshold-based classification of themorphology matching score.

In some cases, however, the overall matching score may fall very closeto a selected threshold value. An overall morphology matching score maynot be sensitive enough to subtle changes in the EGM signal that occurduring some types of VT beats. As a result, a beat may be classified asan SVT beat when it is actually a VT beat, or vice versa, when a fixedthreshold boundary is used for separating VT and SVT beats based on anoverall morphology matching score. In clinical practice, there can besignificant overlap of the morphology scores for VT and SVT beats whichcan result in missed detection of VT or false detection of VT.

As such, during State 2 operations, additional analyses of specific beatfeatures are used in addition to the overall morphology matching scorefor accumulating VT evidence. At block 424, additional beat features areextracted from the EGM signal for the given heart beat. Selected beatfeatures are analyzed to improve the sensitivity and accuracy of SVT/VTdiscrimination. These beat features are referred to herein as “specific”beat features in that these features take a “closer look” at the EGMsignal than the overall morphology score. Specific beat features may beisolated features of the EGM waveform, e.g., relating to amplitude,slope, or other waveform characteristics, occurring at a specific timepoint or a sub-interval within the analysis time window set at block418. In some embodiments, if the FF EGM signal is used to obtain theoverall morphology score, specific beat features may include featuresthat are more spatially localized than the FF EGM signal. For example,an overall morphology score of the NF EGM signal, taken across the sameanalysis window as the FF overall morphology score, may be considered amore specific beat feature than the FF overall morphology score becausethe NF EGM signal is a more spatially localized signal than the FF EGMsignal. As such, specific beat features are features of an EGM signalthat are temporally or spatially more isolated or localized than anoverall morphology score obtained from an EGM signal across the fullduration of a selected analysis time window.

The specific beat features extracted at block 424 are selected based onthe overall morphology matching score result computed at block 422.Specific beat features extracted at block 424 may correspond to beatmorphology parameters generally described in commonly-assigned U.S.patent application Ser. No. 12/415,445, hereby incorporated herein byreference in its entirety. Beat features may be extracted from the NFEGM signal, the FF EGM signal, or a combination of both. Rules areapplied to the overall morphology matching score and the specific beatfeatures to accumulate evidence of VT on a beat-by-beat basis byincreasing or decreasing a VT evidence counter at block 426, as will bedescribed in detail below.

If the VT evidence counter exceeds a treatable rhythm detectionthreshold at block 428, a transition to the convinced State 3 occurs atblock 430. In various embodiments, additional criteria applied to RRIdata must be satisfied in order to make the State 3 transition at block430. If the VT evidence count does not exceed a detection threshold, theprocess advances to the next heart beat at block 432 by returning toblocks 412 and 414 to continue sensing the NF and FF EGM signals.

FIG. 12 is a flow chart 450 of an exemplary method for extractingspecific beat features and accumulating VT evidence on a beat-by-beatbasis. At block 452, the analysis window for the current heart beat isset based on a NF sensed event. At block 454, the FF EGM signal isanalyzed using a desired morphology analysis method, such as Waveletanalysis. A morphology matching score may be computed as a measure ofthe overall match between the FF EGM signal during the analysis windowto a morphology template for a normally conducted beat, i.e. a sinusbeat. A FF overall morphology matching score (FFMS) is computed at block454.

At blocks 460 through 466, the FFMS is compared to different confidencezones for tachycardia discrimination. Multiple zones may be definedincluding, as shown in flow chart 450, an SVT confident zone (block460), an SVT gray zone (block 462), a VT gray zone (block 464) and a VTconfident zone (block 466). Assuming a possible morphology matchingscore of 100, indicating an exact match within the resolution of theanalysis method between an unknown beat and a stored template for anormally conducted beat, an SVT confident zone might be defined as anyscore greater than 85. An SVT gray zone might be defined as a scoreequal to or less than 85 but greater than or equal to 70. A VT gray zonemight be defined as a score less than 70 but greater than or equal to40, and a VT confident zone includes any score less than 40. Otherthresholds may be defined for separating the FFMS zones depending on themorphology matching algorithm being used, clinical data relating to theconfidence levels of morphology scores, clinician preference or otherfactors.

Depending on the zone that the FFMS score falls into, as determined atdecision blocks 460 through 466, specific beat features may be measuredor computed from the EGM signals at a respective blocks 470, 474, 478and 482. The additional specific beat features that are computed arethose needed for applying respective beat feature rules at subsequentblocks 472, 476, 480 or 484. The additional beat features extracted andthe beat feature rules applied according to the morphology matchingscore zone of the current FFMS are selected to enhance the sensitivityand/or specificity of the tachycardia detection algorithm. The FFMSand/or specific beat features will be used to either increase ordecrease a VT evidence counter at block 486 according to which rules areapplied at blocks 472 through 484 and found to be true.

The VT evidence counter is increased or decreased at block 486 inresponse to the outcome of the applied beat feature rule(s). Theinfluence of the FFMS on the accumulation of VT evidence on abeat-by-beat basis can be effectively increased or decreased based onwhich beat feature rule(s) “fire”, i.e., are found true.

If the FFMS falls into an SVT confident due to a high match between theunknown beat and a normal beat template, additional SVT confident zonebeat features are extracted at block 470. The specific beat featuresextracted are those that will be needed for applying the SVT confidentzone beat feature rule(s) at block 472.

The SVT confident zone beat feature(s) may be any feature extracted fromthe FF and/or NF EGM signal during the analysis window and may include amorphology matching score determined from a comparison of the NF EGMsignal of the current unknown beat to a known NF EGM template.

The SVT confident zone beat feature rule applied at block 472 mayinclude threshold comparisons or other criteria which associate theextracted beat feature(s) to either an SVT beat or a VT beat. In oneembodiment, the SVT confident zone beat feature rule(s) are defined toidentify evidence of VT that would contradict the finding of the FFMSbeing in the SVT confident zone. If the rule is satisfied, the VTevidence counter is adjusted accordingly at block 486.

FIG. 13A is a flow chart 500 of the application of an SVT confident zonebeat-feature rule. In one embodiment, a rule for detecting evidence ofan abnormal (VT) beat using the NF EGM signal is applied whenever theFFMS falls into the SVT confident zone. As such, when the FFMS fallsinto the SVT confident zone (block 502), a NF morphology matching score(NFMS) is computed at block 504 for the NF EGM signal within theanalysis window. Additionally or alternatively, specific beat featuresof the EGM signals may be computed or measured at block 504. Anyexamples of specific beat features described herein may be used inapplying a NF abnormal beat rule in the SVT confident zone.

At block 506, the NFMS is compared to VT and SVT detection zones, whichmay be defined the same or similarly to the FFMS detection zones. If theNFMS falls into a zone corresponding to VT, this finding is evidence ofan abnormal beat. This finding based on a “closer look” at the cardiacsignals contradicts the result of the overall FFMS falling into the SVTconfident zone. In other embodiments, specific beat features of the FFand/or NF signals may be extracted and compared to normal templatevalues of the respective features for detecting evidence of a VT beat.

Before declaring the NF Abnormal beat rule to be true at block 518, theFF and/or the NF EGM signals may be examined for noise/artifactcorruption. The results of the noise/artifact rejection process (block512) are used to determine if the FF and NF EGM signals arenon-corrupted signals at decision blocks 510 and 514, respectively.Numerous noise/artifact detection algorithms may be employed forclassifying a heart beat or an EGM strip as noise or artifactcontaminated. In one embodiment, if the FF signal is found to becorrupted at block 510, the current beat is skipped at block 516. The VTevidence counter is not adjusted for the current beat.

If the FF signal is not corrupted, but the NF signal is found to becorrupted (block 514), the NF abnormal beat rule is declared false atblock 508. The NF signal is not used to corroborate or contradict theFFMS result. If the FF and NF EGM signals are not corrupted by noise orartifact, the rule is found true at block 518. This result incombination with the FFMS result is used to adjust the VT evidencecounter.

Referring again to FIG. 12, the VT evidence counter is adjusted at block486 based on the outcome of the NF abnormal beat rule and the FFMS.Generally, the VT evidence counter will be decreased in response to thestrong evidence of an SVT beat based on the FFMS alone. However, thesize of the decrement of the VT evidence counter may be smaller when theNF abnormal beat rule is true. Evidence of an abnormal beat in the NFEGM signal reduces the confidence of the unknown beat being an SVT beatbased on the FFMS alone.

In an illustrative embodiment, the VT evidence counter may be decreasedat block 486 according to the following process when the FF EGMmorphology score falls into the SVT confident zone:

IF NF abnormal beat rule is true, VT evidence is decreased by 0.5

ELSE VT evidence is decreased by 2.0

END

The VT evidence counter is decreased because the FF EGM score was highenough to fall into the SVT confident zone. The VT evidence counter isdecreased by a smaller amount, however, when a NF Abnormal Beat rule isfound to be true and neither of the FF and NF signals is noisecontaminated.

If a NFMS or other specific beat feature(s) are found to be “normal”,i.e. corresponding to a beat that is supraventricular in origin, the NFEGM analysis corroborates the FFMS result. The NF Abnormal beat rulewould be found false, and the VT evidence counter would be reduced froma current value (or remain at a zero value) based on this evidence. If,however, a specific beat feature is “abnormal”, i.e. possibly indicatinga beat that is ventricular in origin, this evidence contradicts the FFMSand effectively reduces the confidence that the beat is an SVT beat. Inthis case, the VT evidence counter may still be reduced but by a smallerdecrement than when both the specific beat feature result and theoverall morphology score support a common finding that the current beatis an SVT beat.

If the FFMS falls in the SVT gray zone (as determined at block 462), SVTgray zone beat features are computed at block 474. In this case,specific beat features are extracted that might provide evidence of a VTbeat, contradictory to the FFMS result that the beat is an SVT beat.Such contradictory evidence may include one or a combination of a verylow NFMS, large differences in specific NF beat features as compared toa corresponding normal template feature, and/or large differences inspecific FF beat features relative to a normal template feature.

SVT gray zone beat features may include specific features of NF and/orFF signals. In one embodiment, the SVT gray zone beat features extractedat block 474 include a maximum slope, an R-wave width, an R-wavesymmetry index (ratio of the upslope to the downslope of the R-wave),and a QR index (ratio of the Q-wave amplitude to the R-wave amplitude).Other features that could be included in various embodiments includeR-wave polarity consistency between the FF and NF signals and/ortemplate R-wave polarity, time difference between NF and FF peakamplitudes, and time difference between NF and FF maximum slopes. It isrecognized that numerous specific beat features could be selected. Thebeat features found to have the highest discriminatory power between SVTand VT beats will be selected for use in applying rules for increasingand decreasing the VT evidence counter on a beat-by-beat basis. Featuresthat are not found to improve the sensitivity or specificity of thetachycardia discrimination algorithm may be ignored.

Rules are applied at block 476 to improve the sensitivity of thediscrimination algorithm to VT. The rules examine specific beat featuresfor evidence of a VT beat that would increase the VT evidence counter atblock 486, rather than decreasing it based on the FFMS result fallinginto the SVT gray zone.

FIG. 13B is a flow chart 520 of one method for applying a VT beat rulewhen the FFMS falls into the SVT gray zone. If the FFMS falls into theSVT gray zone (block 522), the noise/artifact rejection result (block524) for the FF signal is checked at block 526. Additional analysis ofspecific beat features is not performed if the FF signal is corrupted.The entire beat is skipped at block 527, and no adjustment to the VTevidence counter will be made.

If the FF signal is not corrupted, a FF maximum slope is computed atblock 528. If the absolute value of the maximum slope of the FF EGMsignal during the analysis window is less than a low slope threshold(decision block 538), additional analysis is not performed. FF EGMsignal may not be of adequate signal strength to assess specific beatfeatures when the maximum slope of the FF EGM signal is below athreshold value. The VT beat rule is false (block 534).

If the FF signal is not corrupted and meets a minimum slope requirement,additional specific beat features are analyzed to detect evidence of VTwithin the current beat. Either or both of the NF and FF signals may beused for performing additional analysis for detecting evidence of VT.

For example, if the NF signal is determined to be non-corrupted (block532) based on input from the noise/artifact rejection algorithm (block524), the NFMS may be computed at block 536. If the NFMS falls in the VTconfident zone, i.e. a very low match between the NF EGM signal and aknown normal beat template, the VT beat rule fires true at block 544.This evidence of VT in the current beat will be used in adjusting the VTevidence counter.

If the NF EGM signal is corrupted (block 532), or if the NF overallmorphology score is greater than the VT confident zone (block 538),additional analysis of specific beat features extracted from the FFsignal may be performed to detect possible evidence of VT in the currentbeat. For example, FF specific beat features may be measured or computedat block 540 and compared to respective specific beat features measuredor computed from a FF normal beat template at block 542. If any FFspecific beat features are significantly different than the templatebeat features, evidence of VT is detected in the current beat.

In one embodiment, the FF R-wave width, FF R-wave symmetry, and FF ratioof Q-wave amplitude to R-wave amplitude, also referred to herein as QRindex, are each compared to the respective feature of a FF normal beattemplate. A threshold difference between any one of the FF specific beatfeatures and the FF normal beat template will cause the VT beat rule tofire at block 544.

In summary, if the FF signal is corrupted, the entire beat is skippedfor VT evidence adjustment. If the FF signal is not corrupted but doesnot meet a minimum slope requirement, no additional analysis fordetecting evidence of VT is performed. The VT evidence metric isadjusted based on the FFMS at block 486 of FIG. 12. However, if the FFsignal is not corrupted and does meet a minimum slope requirement,specific beat features are examined. The selected beat features may beany features that are known to be altered during a VT beat but perhapsnot enough to cause the overall FFMS to fall into a VT zone. If the FFbeat features are not found to meet VT evidence criteria, the NF EGMsignal may still be used to detect evidence of VT in the current beat.If the NF signal is not corrupted and results in a NFMS in the VTconfident zone, this evidence of VT will be used against the FFMS resultin adjusting the VT evidence counter.

In the illustrative embodiment, specific beat features are not extractedfrom the NF EGM signal for examining for evidence of VT when the overallNFMS is very low. However, it is to be understood that in alternativeembodiments, specific beat features from the NF EGM signal may beexamined for evidence of VT. For example, if the NFMS is higher than theVT confident zone, but still within a gray zone, specific NF beatfeatures may be examined for identifying features indicative of VT.Furthermore, if the NFMS falls into an SVT zone (gray or confident),corroborating the FFMS result, the process shown in FIG. 13B may advancedirectly to block 534 to adjust the VT evidence counter based on theFFMS without further analysis of specific FF beat features.

Referring again to block 486 of FIG. 12, the VT evidence counter isadjusted according to whether the VT beat rule is satisfied or not atblock 476. If the VT beat rule is true, then the VT evidence counter isincreased at block 486 by a predetermined increment. If the VT evidencerule is not true, i.e. no evidence of an abnormal beat is found based onthe additional examination of the FF and/or NF signals, the VT evidencecount is decreased due to the FFMS falling into the SVT gray zone. Inthis case, the VT evidence count is decreased by a decrement that isless than the decrement used to decrease the VT evidence metric when theFFMS falls into the SVT confident zone and there is no evidence of anabnormal beat in the NF signal.

The following process may be used to adjust the VT evidence count whenthe FF overall morphology score falls into the SVT gray zone:

IF VT beat rule is TRUE, increase VT evidence by 0.625

ELSE decrease VT evidence by 0.5

END

The specific values for the increments and decrements applied to the VTevidence count provided herein are illustrative and may be adjusted toprovide optimal sensitivity and specificity of the discriminationalgorithm. Furthermore, it is recognized that numerous variations andsubstitutions of the specific beat features and combinations thereof maybe employed for use in detecting evidence of VT when a FFMS falls intothe SVT gray zone.

If the FFMS falls into the VT gray zone (block 464), specific beatfeatures are computed at block 478, which are needed for applying VTgray zone beat feature rules at block 480. Additional specific beatfeatures are extracted that provide evidence that the current beat ismore likely to be a normally conducted (SVT) beat than a VT beat, incontradiction to the FFMS result. Additionally or alternatively,analysis may be performed to detect supporting evidence that the currentbeat is highly likely to be a VT beat to support the FFMS result.

The specific beat features may be computed from the FF and/or NF EGMsignals and compared to respective template features for a normal beat.In one embodiment, a FF normal beat rule is applied at block 480 fordetecting evidence of normal beat features in the FF signal that wouldcontradict the FF overall morphology score in the VT gray zone. A secondrule, a NF normal beat rule, may also be applied at block 480 fordetecting evidence of normal beat features or overall morphology in theNF signal, which would contradict the FF overall morphology matchingscore and impact the subsequent adjustment of the VT evidence counter.

Beat features computed at block 478 needed for applying a normal beatrule at block 480 may include any features listed herein, including butnot limited to the maximum slope, R-wave polarity, R-wave width, R-wavesymmetry index, ratio of the Q-wave to the R-wave amplitudes, amplitudepeak shift measured as the time difference between the absolute maximumamplitudes of the FF signal and the NF signal, and slope peak shiftmeasured as the time difference between the absolute maximum slope ofthe FF signal and the absolute maximum slope of the NF signal.

FIG. 13C is a flow chart of one method for applying VT gray zone rules.When the FFMS falls in the VT gray zone (block 552), the results of thenoise/artifact rejection algorithm (block 554) are checked to determineif the FF signal is corrupted (at block 556). If the FF signal iscorrupted, the entire beat is skipped with no adjustment to the VTevidence counter as indicated at block 558.

If the FF signal is not corrupted, the FF maximum slope during theanalysis window is computed at block 560 and compared to a low slopethreshold at block 562. If the FF maximum slope is less than the lowslope threshold, no further analysis of FF specific beat features willbe performed. The FF normal beat rule is false (block 566). The processof applying VT gray zone rules proceeds to block 572 to apply a NFnormal beat rule as will be described further below.

If the FF maximum slope exceeds a low slope threshold (block 562), FFspecific beat features are computed at block 564. FF specific beatfeatures may include any beat features listed previously herein. Thespecific beat features used by the FF normal beat rule are selected asthose that may provide evidence that the current beat is likely to be anSVT beat, rather than a VT beat as suggested by the FFMS. The specificbeat features are compared to respective beat features of a FF normalbeat template at block 568.

The FF normal beat rule may require that one or a combination of two ormore specific beat features be within a predefined threshold or range ofthe respective FF normal template feature in order to declare evidenceof an SVT beat. In one embodiment, the FF normal beat rule is declaredtrue at block 570 if the FF QR index, FF R-wave width, and FF R-wavesymmetry index are all within a respective range of the corresponding FFnormal template feature. If any one FF specific beat feature does notmeet a normal beat requirement, the FF normal beat rule is false (block566). In other embodiments, the FF normal beat rule may include “OR”operators that allow the rule to be satisfied if at least one or somespecific beat features are found to approximately match a normal beattemplate.

When the FF normal beat rule is satisfied, there is conflicting evidencefrom the FF overall morphology score, which fell into the VT gray zone,and the specific beat features which provide evidence of SVT. Thiscontradictory evidence will influence the adjustment of the VT evidencecounter at block 486 of FIG. 12, as will be described below.

In addition to the FF normal beat rule, a NF normal beat rule may beapplied to further examine the NF EGM signal for evidence of SVT. Assuch, after determining if the FF normal beat rule is true or false(block 566 or 570), the NF signal is checked to determine if the signalis corrupted at block 572, using the results of the noise/artifactrejection algorithm (block 554). If corrupted, no further analysis ofthe NF signal is performed. The NF normal beat rule is false (block574). The NF signal is not considered reliable for detecting evidence ofan SVT beat that would contradict the FFMS.

If the NF signal is not corrupted, the NFMS is computed at block 576. Ifthe NFMS is very high, e.g. within an SVT confident zone as determinedat block 578, the NF normal beat rule fires true (block 580). The highNFMS is detected as evidence of a normally conducted beat originating ina supraventricular region of the heart. In other embodiments, the NFnormal beat rule may include comparisons of NF specific beat features torespective features of a NF normal template.

Referring again to FIG. 12, the VT evidence counter is adjusted at block486 according to the results of applying the VT gray zone rules. Ifneither of the FF normal beat rule nor the NF normal beat rule is true,then the VT evidence counter is increased by a predetermined incrementin response to the FFMS falling within the VT gray zone. If the FFsignal is corrupted, the entire beat is skipped for VT evidenceadjustment.

If one or both of the FF normal beat rule or the NF normal beat rule arefound to be true, the VT evidence counter may be increased by a smallerincrement or decreased depending on the strength of the evidence of anSVT beat. One example of the process used at block 486 to adjust the VTevidence counter after applying VT gray zone rules is:

IF FF normal beat rule TRUE, decrease VT evidence by 0.375

ELSE IF NF normal beat rule TRUE, decrease VT evidence by 0.5

ELSE increase VT evidence by 0.75.

In this example, the VT evidence is increased only if the FF and NFnormal beat rules are false. If the FF normal beat rule is true, the VTevidence counter is decreased by a relatively small decrement due to theevidence of an SVT beat found in the FF specific beat features. The FFspecific beat features evidencing an SVT beat are given greater weightthan the FFMS falling in the VT gray zone in accumulating VT evidencefor the current beat.

If the NF normal beat rule is true, the VT evidence counter is decreasedby a somewhat larger decrement than if the FF normal beat rule is true.The NF signal evidence for an SVT beat is considered to be strongerevidence of an SVT beat than the FF specific beat feature evidence foran SVT beat and stronger evidence of the correct beat classificationthan the FFMS being in the VT gray zone. It is recognized that thespecific increments and decrements may be given different values invarious embodiments.

The VT evidence metric is adjusted only once for the current beat. Insome embodiments, multiple rules may be applied and the adjustment maybe made based on a single rule considered to have the greatestconfidence in correctly identifying the origin of the current beat. Inother embodiments, the rules may be applied in a hierarchical manner.The first rule that fires is used to determine the increment ordecrement applied to the VT evidence counter. The highest rule thatfires is considered to have the greatest confidence in discriminating VTand SVT. In still other embodiments, a net adjustment to the VT evidencecounter may be determined as a summation of the respective increments ordecrements associated with multiple rules firing for a given beat.

If the FFMS falls into the VT confident zone, as determined at block466, VT confident zone beat features may be computed at block 482 asneeded for applying VT confident zone rules at block 484. In this case,any rules being applied at block 484 may be defined for detectingpossible evidence of an SVT beat that might contradict the finding basedon the FFMS. For example, FF and/or NF specific beat features may becomputed for applying a normal beat rule in the VT confident zone fordetecting evidence indicating that the beat is a normally-conducted SVTbeat. The VT evidence counter may be increased in response to the FFMSfalling into the SVT confident zone. The increment applied to the VTevidence counter, however, may be reduced if a normal beat rule firestrue based on one or more specific beat features, including a NFMS orany other features described herein.

In other embodiments, the VT evidence counter may be adjusted directlyat block 486 when a FFMS falls into a confident zone, either the SVTconfident zone or the VT confident zone. For example, if the FFMS isvery low, i.e. in a VT confident zone, the VT evidence counter may beimmediately increased by one (or another increment) at block 486 withoutextraction of specific beat features and application of beat featurerules. The increment applied to the VT evidence counter in this case islarger than when the FFMS falls into the VT gray zone due to the higherconfidence of a VT beat. Likewise, when the FFMS is very high andfalling into an SVT confident zone, the VT evidence counter may beimmediately decreased without further analysis of beat features. Rulesinvolving specific beat features to improve the sensitivity andspecificity may be applied in “gray” zones only that encompassmid-ranges of the possible range of an overall morphology score.

At block 488, the VT evidence count is compared to a threshold value fordetecting VT. If the VT evidence count reaches a detection threshold, atransition to the convinced State 3 occurs at block 490. If thedetection threshold has not been reached, the algorithm advances to thenext beat at block 492 and returns to block 452 to continue accumulatingVT evidence as long as other criteria for remaining in State 2 aresatisfied.

FIG. 14 is a flow chart 600 of a method for applying rules acrossmultiple FFMS gray zones. In addition or alternatively to thezone-specific rules applied at blocks 472, 476, 480 and 484 of FIG. 12,other rules may be applied across multiple morphology score zones. Forexample, rules may be defined which are applied across the entire grayzone, i.e. the SVT gray zone and the VT gray zone, or across the entireVT zone, i.e. the VT gray zone and the VT confident zone, or across theentire SVT zone, i.e. the SVT gray zone and the SVT confident zone.These rules may examine specific beat features that are consideredstrong evidence of either SVT or VT beat characteristics. If these rulesare found to be true, these rules may override any single zone rules inadjusting the VT evidence counter.

If the FFMS falls into either of the SVT or VT gray zones (whole grayzone), as indicated at block 602, additional EGM signal analysis isperformed to detect the particular situation of VT being initiated by apremature ventricular contraction (PVC) resulting in the onset of thetachycardia rate. Details regarding detection of rate onset aredescribed in U.S. patent application Ser. No. 12/430,301, herebyincorporated herein by reference in its entirety. Briefly, thevariability of n most recent RRIs and the relative change between thesum of those n most recent RRIs and the preceding n RRIs are examined todetect tachycardia rate onset. When the variability is less than avariability threshold and the relative change is greater than a relativechange threshold, the current beat is detected as the tachycardia rateonset beat.

An initiating beat may be several beats earlier, for exampleapproximately 4 to 6 beats earlier, than the tachycardia rate onsetbeat. If an earlier beat preceding the tachycardia rate onset beat is aPVC, the tachycardia is highly likely to be a VT initiated by a PVC. Assuch, for any FFMS falling into the whole gray zone, a PVC strict rateonset rule is applied to enhance sensitivity of the algorithm fordetecting VT.

If tachycardia rate onset is detected for a current beat at block 608,e.g. according to the methods described in the commonly assigned '301U.S. Patent Application, a preceding beat is checked for characteristicsthat would indicate that the preceding beat that is ventricular inorigin. A single preceding beat may be examined, such as the fourth beatearlier than the current RRI. In alternative embodiments, one or morepreceding beats may be examined for evidence that an initiating PVC hasoccurred within several beats prior to the tachycardia rate onsetdetection.

At blocks 610 through 614, multiple specific beat features of apreceding beat are compared to the respective beat features of a normaltemplate. In the illustrative embodiment, all of these beat features arerequired to be significantly different than the normal beat template inorder to determine that the beat has a high likelihood of being a PVC,initiating the tachycardia rate.

The specific beat features examined at blocks 610 through 614 may varybetween embodiments. In the flow chart 600, the R-wave polarity, slopepeak shift, R-wave width, and QR index are compared to the normaltemplate at blocks 610, 612 and 614. If all of these features representa change from the normal template, the PVC strict rate onset rule firestrue at block 620. If any one of the FF specific beat features is notsignificantly different than the normal template, the FF specific beatfeature evidence of a PVC-initiated VT is not strong enough to overrideother VT or SVT evidence provided by the overall FFMS result andzone-specific rules.

If the FF specific beat features do not provide evidence of VT at blocks610 through 614, however, the NFMS may additionally be checked at block616 to detect evidence of an initiating PVC. When both the NFMS and theFFMS of a preceding beat fall within the VT confident zone, the PVCstrict rate onset rule will be satisfied (block 620). If neither the FFspecific beat features (blocks 610 through 614) nor the NFMS and FFMS(block 616) meet the rule criteria, the PVC strict rate onset rule isfalse at block 606.

If the PVC strict rate onset rule fires true at block 620, this resultmay override other rules applied to single FFMS zones in adjusting theVT evidence counter. In one embodiment, the VT evidence counter isincreased to a maximum value (e.g. 8) at block 622 in response to thePVC strict rate onset rule being true. If the PVC strict rate onset ruleis false, the FFMS and corresponding zone-specific rule(s) are used todetermine the adjustment to the VT evidence counter for the currentbeat.

FIG. 15 is a flow chart 625 of a process for applying a rule fordetecting a rhythm breaking point, which may be applied across multipleFFMS zones. Interval-based tachycardia detection methods often require aspecified number of RRIs out of a previous number of most recent RRIs,e.g. 18 out of 24 intervals, to be shorter than a tachycardia detectioninterval in order to detect tachycardia. This allows a small number ofthe most recent RRIs to be longer than the tachycardia detectioninterval and still appropriately detect tachycardia in the presence ofundersensing. In some cases, however, a long RRI may be an actual pausein the rhythm rather than the result of undersensing. Detection of anactual long pause is useful information in detecting a break orspontaneous termination of a tachycardia rhythm.

A long pause or two consecutive normal beats marking a break in thetachycardia rhythm may occur during atrial fibrillation, recurrentnon-sustained VT, or other non-treatable rhythms. Two consecutive normalbeats or a long pause may also be detected when a concerning rhythm isthe result of T-wave oversensing. As such, it is desirable to detect anactual long RRI and/or normal R-wave morphology on two consecutive beatssuch that a rhythm breaking point can be identified and used to avoidprogression to detection of a treatable tachycardia and therapy deliverywhen the rhythm is non-sustained or a non-treatable rhythm.

Generally, at any time during a detection algorithm, a long RRI may bedetected at block 626. Criteria for detecting a long RRI may be based ona percentage of the previous RRI and/or an average of a specified numberof the most recent RRIs. For example, if the current RRI is at least 25%longer than the previous RRI and is longer than the average, maximum, oranother metric of the most recent 8 RRIs (or another number of mostrecent RRIs), a long RRI is detected. An additional or alternativerequirement may be that the RRI is longer than a minimum thresholdinterval. Various criteria may be applied for detecting a long RRI butwill typically include a comparison to the previous RRI and/or a metricof the most recent RRIs.

At blocks 628 and 632, additional analysis of the EGM signal(s) isoptionally performed to detect evidence supporting the detection of anactual long RRI or evidence of undersensing that would indicate the longRRI is due to undersensing. At block 628, the EGM signal(s) are examinedfor evidence of an undersensed R-wave occurring during the long RRI.Evidence of an undersensed R-wave may include a maximum slew rateexceeding a threshold, a maximum amplitude exceeding a threshold, and/orother signal features occurring during the long RRI that may correspondto a QRS complex. For example, if the signal amplitude exceeds apredetermined percentage of the most recent sensed R-wave amplitude, anintervening R-wave may have been undersensed resulting in a falsedetection of a long RRI. In a specific example, if an amplitude greaterthan approximately 25% of the current R-wave amplitude is found duringthe detected long RRI, an undersensed R-wave may be present. Amplitude,slew rate or other signal morphology evidence of an undersensed eventmay be detected or obtained from the same EGM signal or a different EGMsignal than the one used to detect the long RRI.

Additionally or alternatively, another EGM sensing vector may be checkedat block 628 to verify that a sensed event did not occur on anothersensing vector during the detected long RRI. For example, if the longRRI is detected on the NF EGM signal, the FF EGM signal is checked toverify that a sensed event did not occur on the FF EGM signal during thelong RRI on the NF signal. A FF sensed event occurring within a shortinterval of time with respect to a NF sensed event may correspond to thesame beat. Thus the interval examined on the FF EGM signal for detectingevidence of an undersensed R-wave on the NF EGM signal may be defined tobe a truncated or narrower interval within the NF long RRI. For example,an interval beginning approximately 50 to 80 ms after the previous NFsensed event and ending approximately 50 to 80 ms earlier than thecurrent NF sensed event may be examined for FF sensed events. If a FFsensed event does not occur during the interval, the long RRI is likelyto be an actual long pause that may be detected as a rhythm breakingpoint.

In a similar manner, a long RRI measured on the FF EGM signal may beverified by checking whether a sensed event occurs within acorresponding truncated interval on the NF EGM signal. A variation ofthe method of searching for a sensed event during a truncated intervalis to determine if sensed events occur on two different EGM signals in a1:1 ratio of an interval encompassing one or more RRIs on the first EGMsignal. For example, if three events occur on the FF signal during aninterval encompassing a single RRI on the NF signal, undersensing on theNF signal may be suspected.

If there is evidence of an undersensed R-wave during the long RRI, e.g.,based on a high slew rate, high amplitude, sensed event on anothersensing vector or other signal features during the long RRI, a rhythmbreaking point is not detected and the tachycardia detection algorithmcontinues at block 630. Any pending therapies may proceed. If there isno evidence of an undersensed R-wave, the sensed event morphology maybeanalyzed at block 632 to verify that the R-wave ending the long RRIrepresents a normal R-wave morphology. A morphology matching score maybe computed, and a high matching score of the R-wave ending the long RRIis detected as a rhythm breaking point at block 634.

The morphology matching score required to detect the rhythm breakingpoint may be dependent on the length of the long RRI. A thresholdmorphology matching score required for detecting a rhythm breaking pointfor different ranges of RRIs may be stored in a look-up table or may bedefined as an exponential or other relationship between the matchingscore and the RRI. To illustrate, if the RRI is only slightly longerthan the previous RRI or an average of recent RRIs, for example up toapproximately 25% longer, a very high morphology matching score may berequired to detect a rhythm breaking point, e.g. within an SVT confidentzone. If the long RRI is much longer than the previous RRI or an averageof recent RRIs, for example more than approximately 50% longer, a lowermatching score, e.g. a score in the SVT gray zone, may be accepted asevidence of a rhythm breaking point.

In one specific embodiment, if the current RRI is at least approximately25% greater than the previous RRI and the average of the most recent 8RRIs and is at least 350 ms long, a rhythm breaking point is detectedwhen the morphology matching score of the QRS signal that ends the longRRI is greater than 35/RRI, wherein RRI is the current RRI in secondsand the morphology matching score ranges from 0 to 100.

It is contemplated that one or both of blocks 628 and 632 may beperformed when a long RRI is detected for verifying a rhythm breakingpoint. At block 640, a response to the rhythm breaking point isprovided. The response to detecting a rhythm breaking point may includeaborting a therapy, delaying a therapy, resetting an initiated menu oftherapies to an earlier therapy in the menu sequence, clearing counts orother evidence of VT, augmenting evidence of SVT, changing aclassification of the current rhythm, or ending a measurement of therhythm episode duration and resetting an episode timer.

The detection of a long pause may occur during any state of thedetection algorithm, including the convinced State 3, and the responseto detecting the long pause as a rhythm breaking point may vary betweenstates as appropriate.

With regard to the tachycardia detection algorithm State 2 operations,the VT evidence counter may be set to zero in response to a pausedetection. If any therapies have been delivered during the currenttachycardia episode, the next scheduled therapy will be reset to thefirst therapy of a programmed menu of therapies. As a result, the nexttherapy delivered upon reaching State 4 again will be the first therapyof a selected menu of therapies rather than a progression to a moreaggressive therapy.

The method for detecting a rhythm break may be implemented in anytachycardia detection algorithm and is not limited to use in therule-based detection algorithm described herein. The process ofmonitoring for a long RRI and analyzing the long RRI for evidence ofundersensing and/or for evidence of a normal beat concluding the longRRI may be performed for detecting a rhythm breaking point in anytachycardia detection algorithm.

FIG. 16 is a flow chart 650 of one method for applying a rule fordetecting a rhythm breaking point across the whole SVT zone. In thisexample, a Rhythm breaking point rule is applied when the FFMS fallsinto either the SVT confident zone or the SVT gray zone. The Rhythmbreaking point rule is applied to detect any beat that is normal with ahigh degree of confidence. A normally conducted beat associated with along pause or two consecutive normal beats may be an indicator of abreak in a tachycardia rhythm.

If the FFMS for the current beat falls into the whole SVT zone (block652), the previous FFMS is checked at block 654. If the FFMS for boththe current and previous consecutive sensed events are within the SVTconfident zone, the NFMS is computed at block 655. As long as the NFMSfor the current beat is greater than zero (or another predeterminedthreshold) at block 656, the two consecutive FFMS in the SVT confidentzone provide evidence of a rhythm break. The Rhythm breaking point rulefires true at block 670.

If the current and previous FFMS do not both fall into the SVT confidentzone (i.e., one or both falls into SVT gray zone or lower), the currentRRI is analyzed to detect a long pause in the tachycardia rhythm. Ingeneral, if the current RRI is determined to be longer than previousRRIs, the current RRI may represent a long pause and a rhythm breakingpoint. In one embodiment, the current RRI is compared to a movingaverage of recent RRIs, for example the most recent eight RRIs, at block658. The current RRI may be required to be longer than RRI movingaverage or any factor of the RRI moving average. For example theweighting factor “M” in block 658 may be equal to 1 or a higher value.

If the current RRI is longer than the moving average, or a requiredpercentage longer than the moving average, the current RRI may also becompared to the most recent preceding RRI at block 662 to verify a longpause. The current RRI is required to be longer than the preceding RRIby a predetermined factor or percentage. The weighting factor “N” inblock 662 may be equal to approximately 1.3, for example, or anotherselected value greater than 1. If the current RRI is not likely to be along pause based on a negative result of either of the comparisons atblocks 658 and 662, the Rhythm breaking point rule is not satisfied anddeclared false at block 660.

If the current RRI is longer than the preceding RRI, for example atleast approximately 30% longer than the preceding RRI, FF specific beatfeatures are examined at block 666 to determine if the beat concludingthe long RRI is a normal beat. Various FF specific beat features may beexamined to determine if the specific beat features closely matchcorresponding specific beat features of a normal beat template at block666. In one embodiment the FF R-wave symmetry index, FF R-wave width,and FF QR Index are each compared to the respective features of a FFnormal beat template. If each of these features falls within anacceptable threshold range of the normal beat template, the Rhythmbreaking point rule is satisfied and declared true at block 670. Thecombined evidence of a long RRI, FFMS in the whole SVT zone, andspecific FF beat feature evidence of a normally conducted R-wavesuggests that the current beat is a rhythm breaking point. It is to beunderstood that in various embodiments, the FFMS, FF specific beatfeatures, the NFMS and/or NF specific beat features may be used alone orin any combination for determining that the ending R-wave of the longRRI is highly likely to be a normal beat.

If the Rhythm breaking point rule is true, this result may overrideother single zone rules and the FFMS in adjusting the VT evidencecounter. In one embodiment, the VT evidence counter is cleared to a zerovalue at block 672 in response to the Rhythm breaking point rule beingtrue.

If more than one multiple zone rules are included in the tachycardiadetection algorithm, the multiple zone rules may be performed in ahierarchical order such that a highest level rule that fires trueoverrides the results of lower level rules in causing adjustment to theVT evidence counter. Multiple zone rules may be written such that theyare mutually exclusive, i.e. there is no possibility of more than onemultiple zone rule firing simultaneously. For example, a whole gray zonerule and a whole SVT zone rule may be written such that both rulescannot be satisfied for a current RRI. In other embodiments, anadjustment to the VT evidence counter in response to a multiple zonerule firing true may be made only when a single multiple zone rule firestrue and all others are false. In this case, if more than one multiplezone rule fires true, the multiple zone rules may be consideredinconclusive, and the results of the single zone rules and FFMS arerelied upon for adjusting the VT evidence counter.

Alternatively, if multiple rules apply to a particular FFMS zone, whichmay include single zone and/or multiple zone rules, the rules may beapplied in a predefined sequence such that a lower level rule is onlyapplied if all higher level rules are false. The VT evidence counter isadjusted as soon as a rule fires for a given FFMS zone.

FIG. 17 is a flow chart 800 of a process for adjusting a VT evidencecounter on a beat-by-beat basis in response to FFMS zone rules foraccumulating evidence for detecting a treatable tachycardia. The processshown in flow chart 800 determines the appropriate increment ordecrement applied to a VT evidence counter for a given beat in responseto applied beat feature rule(s). Other criteria that may be applied fordeciding if the VT evidence counter should be adjusted and by how much,such as verifying that the FF EGM signal is not corrupted, are not shownin FIG. 17. It is recognized, however, that other criteria may beapplied before making any adjustment to the VT evidence counter. If, forexample, the FF EGM signal is corrupted, the beat may be skippedentirely with no adjustment to the VT evidence counter.

In the process shown, the rhythm breaking point rule is applied when theFFMS falls into the whole SVT zone, i.e. the SVT confident zone 802 orthe SVT gray zone 804. Application of one embodiment of a rhythmbreaking point rule is described above in conjunction with FIG. 16. Therhythm breaking point rule is a higher level rule than zone-specificrules. As such, if the rhythm breaking point rule is found true atdecision block 810, The VT evidence counter is adjusted at block 834without applying additional zone-specific rules. In the illustrativeexample, the VT evidence counter is cleared to a zero value in responseto the evidence of a rhythm breaking point, i.e. a non-sustainedtachycardia.

When the rhythm breaking point rule is false and the FFMS falls into theSVT confident zone (upper branch of block 810), the process proceeds toblock 814 to apply beat feature rules specific to the SVT confidentzone. In the illustrated embodiment, the NF abnormal beat rule isapplied at block 814, as described above in conjunction with FIG. 13A.When the NF Abnormal beat rule is false, the VT evidence counter isdecreased at block 832. The strong evidence of an SVT beat based on theFFMS and the lack of evidence of a VT beat based on the NF abnormal beatrule result justifies a relatively large decrement of the VT evidenceaccumulation. In this example, the VT evidence counter is decreased by 2at block 832.

If the NF abnormal beat rule is true at block 814, evidence thatcontradicts the result of the overall FFMS has been found in specificbeat features. The VT evidence may still be decreased in response to theFFMS falling into the SVT confident zone, but by a smaller decrementthan when the NF abnormal beat rule is false. At block 830, VT evidencecounter is decreased, for example, by 0.5.

When the rhythm breaking point rule is false (block 810) and the FFMSfalls into the SVT gray zone (lower branch of block 810), the processmoves to block 816 to apply zone specific rules for the SVT gray zone.In one embodiment, the VT beat rule is applied at block 816 as describedabove in conjunction with FIG. 13B. When the VT beat rule is false, theVT evidence counter is decreased by 0.5 at block 838 in response to theFFMS falling into the SVT gray zone and the lack of specific beatfeature evidence for a VT beat. The VT evidence accumulation isdecreased at block 838 by a smaller decrement than when the FFMS fallsinto the VT confident zone with no evidence of an abnormal beat.

When the VT beat rule is true at block 816, the combination of the FFMSbeing in the SVT gray zone and the contradictory evidence of a VT beatbased on the specific beat features results in an increase in VTevidence at block 836. In the illustrated example, the increment appliedat block 836 is 0.625.

In addition to applying the rhythm breaking point rule when the FFMSfalls into the SVT gray zone, the PVC strict rate onset rule is appliedat block 812 whenever the FFMS falls into the SVT gray zone (block 804).The PVC strict rate onset rule is also a multiple zone rule and isapplied across the entire gray zone, including both the SVT gray zone(block 804) and the VT gray zone (block 806). If the PVC strict rateonset rule is true at block 812, VT evidence is immediately adjusted atblock 840 without applying any single zone rules. The VT evidencecounter is maximized in one embodiment in response to the PVC strictrate onset rule being true.

As mentioned previously, the multiple-zone rules applied at blocks 810and 812 may either be written in an exclusive manner such that only asingle rule can be true for a given beat, or the multiple-zone rules maybe applied in a hierarchical manner such that only the VT evidencecounter is immediately adjusted in response to the first rule firing.Alternatively, an additional step may be included in the flowchart 800for verifying that other multi-zone rules are false before adjusting theVT evidence in response to a multi-zone rule being true. These variousoptions are not shown in FIG. 17 for the sake of clarity. In general,the VT evidence metric is adjusted in response to a single rule firingand is not adjusted more than once for a current heart beat.

If the PVC strict rate onset rule is false when the FFMS falls into theSVT gray zone at block 812 (upper branch), the zone-specific rule forthe SVT gray zone is applied at block 816 as described above. If theFFMS falls into the VT gray zone and PVC strict rate onset rule is falseat block 812 (lower branch), the single zone rule for the VT gray zoneis applied at block 818. In this example, the FF normal beat rule isapplied as described above in conjunction with FIG. 13C. If the FFnormal beat rule is true, this evidence of an SVT beat overrides theinfluence of the FFMS falling into the VT gray zone in adjusting the VTevidence counter. The VT evidence is decreased by a relatively smalldecrement at block 842 in response to the FF normal beat rule being truein contradiction to the FFMS falling into the VT gray zone.

In this example, more than one zone-specific rule may be applied for agiven FFMS zone. For the VT gray zone, if the FF normal beat rule is nottrue at block 818, the NF normal beat rule as described in conjunctionwith FIG. 13C above is also applied at block 820. When evidence of anormal beat is found in the NF signal, this result overrides theinfluence of the FFMS falling into the VT gray zone on VT evidenceaccumulation. VT evidence is decreased at block 844 in response to theNF normal beat rule being true rather than being increased in responseto the FFMS being in the VT gray zone. It is recognized that the FFnormal beat rule (block 818) and the NF normal beat rule (block 820) maybe applied in a different hierarchical order such that the VT evidenceis adjusted based on the first rule to fire true.

In this example, the NF normal beat evidence is considered strongerevidence of an SVT beat than the FF normal beat evidence. As such, theVT evidence is decreased by a larger decrement in response to the NFnormal beat rule being true than the FF normal beat rule being true.

If the whole gray zone PVC strict rate onset rule (block 812) is falseand the single zone rules (blocks 818 and 820) applied to the VT grayzone are all false, the VT evidence counter is increased at block 846.Because the FFMS is in a VT gray zone rather than the VT confident zone,the increment applied to the VT evidence counter is relatively small,e.g. 0.75.

When the FFMS falls into the VT confident zone (block 808), the VTevidence counter is immediately increased by 1 at block 848. In otherembodiments, zone-specific rules may be applied for the VT confidentzone. However, in the illustrated embodiment, the FFMS being very low isconsidered strong evidence of a VT beat warranting a relatively largeincrease in the VT evidence accumulation.

It is contemplated that differently sized increments/decrements may beselected for use at the various blocks 830 through 848 based on thedegree of confidence provided by the application of a given rule. Thedegree of confidence in separating VT and SVT beats for a given rule maybe determined through clinical evaluation.

After adjusting the VT evidence counter at one of blocks 830 through848, the VT evidence counter is compared to a detection threshold atblock 850. If the VT evidence counter meets or exceeds the detectionthreshold, e.g. a threshold of 6 in one embodiment, a transition to theconvinced State 3 occurs at block 854. If the VT evidence metric has notreached the detection threshold at block 850, the detection algorithmremains in State 2 and advances to the next beat at block 852 tocontinue accumulating VT evidence. The detection threshold applied tothe VT evidence counter may vary between embodiments and may be tailoredfor a specific patient. The threshold will also depend in part on thesize of the various increments/decrements applied in response to thevarious beat feature rules and FFMS zones.

FIG. 18 is a flow chart 860 of a method for classifying a current beatas a corrupted or non-corrupted signal in a noise/artifact rejectionprocess. The process shown in FIG. 18 is performed to excludenon-physiological signals from interfering with correct rhythmclassification. The method shown in flow chart 860 may correspond to thenoise/artifact rejection process represented by blocks 512, 524, and 554in FIGS. 13A-C, respectively. As described above, a current beat may beskipped and not used in updating the VT evidence counter when the FF EGMsignal is identified as a corrupted beat (see for example, block 510 ofFIG. 13A, block 526 of FIG. 13B and block 556 of FIG. 13C). A beatfeature rule that utilizes a NFMS or features extracted from the NF EGMsignal may be false if the NF EGM signal is corrupted (see for exampleblock 514 of FIG. 13A, block 532 of FIG. 13B and block 572 of FIG. 13C).

In order to classify a current beat as a corrupted signal for rejectingthe current beat in accumulating VT evidence or deciding a specific beatfeature rule is false, one or more cardiac cycles or an n-second segmentof the EGM signal may be examined to detect the presence ofnon-physiological signals. In other words, classification of the currentbeat as being noise corrupted is not limited to examining a current RRIof the EGM signal of interest but may include examining a longer EGMsignal interval to detect presence of noise that may interfere withcorrect rhythm classification.

The process shown in flow chart 860 may be applied to the FF EGM signalor the NF EGM signal or both signals. At block 862 a cardiac event issensed for use in setting a noise corruption analysis window at block864. In one embodiment, a NF event is sensed for setting a one-secondwindow applied to both the FF and NF EGM signals for detecting noisecorruption. The n-second window is set to extend n-seconds earlier thanthe currently sensed event and end upon the NF event. The predefinednoise corruption analysis window duration is typically set to be longerthan RRIs, for example at least one second in duration, such that therewill be overlap between the n-second noise analysis windows from onebeat to the next.

At block 866, gross morphology parameters are computed for the FF and/orNF EGM signal during the n-second window. The parameters computed fordetecting noise corruption can be referred to as “gross morphology”parameters in that these parameters can be computed over the entirety ofan n-second signal segment without limiting the analysis to themorphology analysis window used for computing an overall morphologyscore. EGM signal baseline, T-wave or other signal segments and evenmore than one QRS complex may be included in the n-second window usedfor measuring gross morphology parameters. The “gross” morphology of theEGM signal is used to detect noise/artifact corruption since noiseartifact may appear at any time in the EGM signal and is not limited toa window of time corresponding to a QRS waveform. Even though there maybe considerable overlap between consecutive n-second segments, only thecurrent RRI that ends with the sensed event that triggered the currentn-second noise analysis window is classified as being corrupted ornon-corrupted based on the noise information contained in the currentn-second segment. The noise classification of other previous RRIsfalling within the n-second segment is not affected by the noiseclassification resulting from gross morphology analysis of the currentn-second segment.

Gross morphology parameters used to detect the presence ofnon-physiological noise may include a noise-to-signal ratio (NSR) (orconversely a signal-to-noise ratio), a mean period (MP), and metricsrelated to muscle noise content and signal characteristics associatedwith lead-related conditions. These parameters are used to rejectsignals contaminated by high frequency noise, significant muscle noise,and characteristic lead-related artifact. The noise/artifact rejectionprocess may include methods generally disclosed in commonly-assignedU.S. Publication No. 2007/0239048, hereby incorporated herein byreference in its entirety.

At block 868, the current HR is determined using at least the currentRRI, all of the RRIs occurring during the n-second strip or a current HRestimate as described above based on the nth shorted RRI out of the mostrecent m RRIs. If the HR is greater than an SVT limit (block 870), noisedetection rules for use during a high heart rate are applied at block874. If the HR is less than an SVT limit, a different set of noisedetection rules may be applied for heart rates slower than the SVT limitat block 872.

The gross morphology parameters used for detecting a corrupted signaland/or the thresholds applied to those gross morphology parameters maybe dependent on an estimate of the current heart rate. Different noisedetection criteria may be applied for detecting noise corruption duringheart rates above the SVT limit than during heart rates below the SVTlimit. Generally, during HRs greater than the SVT limit, more stringentnoise corruption criteria are applied. For example, higher thresholdsmay be applied to the gross morphology parameters for detecting noisecorruption.

If any of the gross morphology parameters exceed a noise corruptionthreshold, as determined at block 876, the signal is classified as acorrupted signal at block 880. If none of the parameters exceed thenoise corruption thresholds applied based on heart rate, the signal isnon-corrupted as indicated at block 878. Noise detection parametersincluding a mean period, metrics of muscle noise, and/or a NSR asgenerally disclosed in the above referenced '048 published applicationmay be compared to noise detection thresholds at block 876. Differentcriteria may be applied to FF and NF signals for classifying the signalas corrupted or non-corrupted.

As described in conjunction with FIG. 13A through 13 C, if the FF signalis found to be corrupted for the current RRI interval (using then-second segment), the VT evidence counter will not be adjusted for thecurrent beat. If the FF signal is found to be non-corrupted the VTevidence counter may be adjusted according to the FFMS zone and theresults of any beat feature rules applied for the zone. If the beatfeature rule involves analysis of the NF EGM signal, the rule may befound false if the NF EGM signal is classified as corrupted at block 880for the current heart beat.

At block 882, a count of the number of n-second segments that have beenclassified as non-corrupted out of a specified number of the most recentsegment is maintained. In one embodiment, if at least half of then-second segments are classified as non-corrupted, e.g. at least fourout of the most recent eight n-second segments, a treatable rhythm flagis set high at block 884. This treatable rhythm flag may be required tobe high in order to allow a transition from State 2 to the convincedState 3. The treatable rhythm flag is an indication that the EGM signalbeing analyzed is considered to be a clean enough signal for thepurposes of reliably classifying the rhythm as a treatable rhythm whenother state transition criteria are also satisfied. For example, in oneembodiment, if both the NF and the FF HR estimates exceed the SVT limitand a NF treatable rhythm flag and a FF treatable rhythm flag are sethigh, a transition to the convinced State 3 may occur. This transitionbased on both the NF and FF HRs exceeding the SVT limit may occur evenif the VT evidence counter has not crossed a detection threshold.

If more than half (or another percentage) of the most recent n-secondsegments are classified as corrupted, the treatable rhythm flag for thecorresponding EGM signal is set low at block 886. In this case, even ifother criteria are met for transitioning from the concerned State 2 tothe convinced State 3, a state transition may not occur due to thecorruption of the EGM signal. For example, if the NF and FF HR estimatesexceed an SVT limit for advancing to the convinced State 3, but one ofthe NF or the FF EGM signal treatable rhythm flag is set low, the statetransition will not occur. The treatable rhythm flag must be set highfor at least one or both the FF and NF EGM signals based on therespective signal being classified as non-corrupted before the detectionalgorithm will advance to the convinced State 3.

In some embodiments, reliance on a “primary” EGM signal may be switchedbetween the NF and FF EGM signals based upon the status of the treatablerhythm flag. For example, if the NF EGM signal is found noise-corruptedand the NF treatable rhythm flag is set low, the FF EGM signal maybecome the primary signal for sensing cardiac events, setting amorphology analysis, and computing an overall morphology matching score.When the NF EGM signal is found to be non-corrupted again, i.e. the NFtreatable rhythm flag is set high, its role as primary sensing signalfor sensing cardiac events and setting a morphology analysis window isrestored again.

If the FF EGM signal is found noise-corrupted, and the FF treatablerhythm flag is set low, the NF signal may be used for computing anoverall morphology matching score until the FF treatable rhythm flag isagain set high. Likewise, specific beat feature rules may be appliedusing beat features derived from only an EGM signal having a treatablerhythm flag set high. For example, FF signal features may be substitutedin a specific beat feature rule that normally relies on NF signalfeatures and vice versa.

In one embodiment, if the FF EGM signal is corrupted, instead ofskipping the beat for the purposes of VT evidence accumulation asdescribed above in conjunction with FIGS. 13A-13C, the NFMS may becomputed. If the NFMS is in a confident zone, the VT evidence counter isadjusted in response to the NFMS zone. If the NFMS is in a gray zone,the VT evidence counter is not adjusted and the beat is skipped. The VTevidence counter may be adjusted by a relatively smaller increment ordecrement in response to a NFMS confident zone (when FF EGM iscorrupted) than the increment or decrement applied in response to a FFMSconfident zone (when FF EGM is non-corrupted). In an illustrativeexample, the VT evidence counter may be increased by 0.75 instead of by1 when the NFMS is in the VT confident zone and the FF EGM signal isfound to be corrupted. The VT evidence counter may be decreased by 1.5instead of by 2 when the NFMS is in the SVT confident zone and the FFEGM signal is corrupted.

FIG. 19 is a flowchart 900 of one method for computing metrics of leadartifact for use in classifying an EGM signal as corrupted ornon-corrupted. The process shown in flowchart 900 may be performed oneither of the FF or the NF EGM signals or both for use in classifyingthe respective signal as corrupted or non-corrupted as part of thenoise/artifact rejection process shown in FIG. 18. At block 902, acardiac event (R-wave) is sensed on the NF EGM signal for setting then-second noise analysis window at block 904.

At block 906, all of the zero crossings during the n-second segment arelocated. Sample points immediately adjacent to each zero crossing areidentified. The amplitude of the adjacent sample point before a zerocrossing and the amplitude of the adjacent sample point after the samezero crossing are compared. The sample point adjacent to each zerocrossing having the smallest absolute amplitude is set to a zeroamplitude at block 908 in order to anchor the point to a zero value fordemarcating the positive- and negative-going pulses in the n-secondnoise analysis window.

The n-second signal segment is then rectified at block 910. The maximumamplitude of the rectified signal is determined, and a predeterminedpercentage or portion of the maximum rectified signal amplitude, forexample half the maximum rectified signal amplitude, is computed atblock 912 as a pulse amplitude threshold. All rectified signal samplepoints having an amplitude greater than half (or another percentage) ofthe maximum rectified signal amplitude are counted at block 914. Thiscount is stored as a noise artifact metric, metric 1, at block 916. Inone embodiment, the noise artifact metric is used as a measure oflead-related artifact. The percentage or portion of the maximumrectified signal amplitude used as a pulse amplitude threshold may bedefined based on the HR, which may be estimated using any methodsdescribed herein. When the HR is greater than the SVT limit, morestringent noise detection criteria may be applied by selecting a largerportion of the maximum rectified signal amplitude as a pulse amplitudethreshold for computing the noise artifact metric 1.

At block 918, a single pulse within the rectified signal having themaximum number of sample points exceeding half (or another percentage)of the maximum rectified signal amplitude is identified. To identifythis single pulse, the sample points in each individual pulse during then-second segment that exceed half of the maximum rectified signalamplitude are counted. The count for each individual pulse is thencompared to the count for every other pulse. The pulse having themaximum number of sample points exceeding half of the maximum rectifiedsignal amplitude is identified as the pulse having a maximum pulsewidth. The number of points exceeding half of the maximum rectifiedsignal in the maximum pulse width pulse is stored at block 920 as asecond lead artifact metric.

At block 922, the lead artifact metric is compared to a corrupted signalthreshold defined as a function of the second lead artifact metric,“metric 2”. For example, the lead artifact metric 1 may be compared to athreshold defined as W*(metric 2−x). The terms “W” and “x” used here arenot necessarily equal to or related to other equation terms identifiedherein by the same letter. The weighting factor “W” and/or term “x” maybe set based on heart rate, e.g. based on whether the current HRestimate exceeds the SVT limit as described in conjunction with FIG. 18.The noise threshold may be set to a higher value by increasing “W” andor “x” when the HR is greater than the SVT limit to create morestringent noise detection criteria.

In one embodiment, if the total number of sample points in the rectifiedsignal exceeding half of the maximum amplitude is more than ten timesgreater than the number of sample points in a single pulse that exceedhalf of the maximum amplitude, the signal is classified as corrupted forthe current beat at block 926. If the lead artifact metric does notexceed a corrupted signal threshold at block 922, other gross morphologymetrics may be analyzed at block 924 before classifying the EGM signalas corrupted or non-corrupted for the current beat. Other grossmorphology metrics may include a NSR, a mean period, and a metricrelated to muscle noise as mentioned previously.

FIG. 20 is a flowchart 700 of a method for transitioning betweendetection states. The method for transitioning from State 1, theunconcerned state, to concerned State 2 has been discussed previously.Once State 2 is entered at block 702, VT evidence is accumulated on abeat-by-beat basis. If the VT evidence counter does not reach thedetection threshold, as determined at block 704, conditions fortransitioning back into State 1 are examined beginning at block 706. Ingeneral, if the HR decreases and the VT evidence has fallen below atermination threshold, the detection algorithm may transition back intothe unconcerned State 1. The transition criteria may be dependent onwhether the transition into State 2 from State 1 occurred during the LVmode of operation or the HV mode of operation in State 1. The flow chart700 provides one illustrative method that may be used to control thetransition from State 2 back to State 1.

At block 706, the current RRI is compared to a detection lower limitinterval. If the RRI is longer than a detection lower limit interval, aswitchback counter is increased at block 716. The switchback counter isused to track consistently long RRIs (i.e. greater than the detectionlower limit interval) for controlling transition back to State 1.

If the RRI is not greater than the detection lower limit interval, andState 2 was entered from State 1 during the LV mode of operation (asdetermined at block 712), the current RRI is compared to the storedexpected RRI range at block 714. As described previously, the expectedRRI range at the time of transitioning from State 1 to State 2 is frozenat its current value and stored for use in controlling transition backto State 1. If the current RRI is not within the expected RRI range atblock 714, the switchback counter is decreased at block 708.

Additionally, a slow beat counter is decreased at block 710. The slowbeat counter is a separate counter from the switchback counter and isalso used to count “slow” heart beats. The slow beat counter is used totrack consistently slow beats during States 2 and 3 and used to controltransition from State 3 directly back to State 1 as will be describedfurther below. The switchback counter and slow beat counter may bedecreased by one, two or another selected decrement in response to anRRI that is shorter than the detection lower limit and not within theexpected RRI range for a normal heart rhythm.

An RRI that is shorter than the detection lower limit and still outsidea normal expected RRI range is evidence that the current rhythm is stilla concerning rhythm and no state change is warranted. After decreasingthe slow beat counter, the detection algorithm remains in State 2 byreturning to block 702. The rhythm is still considered a concerningrhythm.

Returning to block 714, if the current RRI is within the stored expectedRRI range for a normal heart rhythm, the switchback counter is increasedat block 716. At block 718, the slow beat counter is also increased inresponse to an RRI longer than the detection lower limit (block 706) oran RRI within the expected RRI range when the transition to State 2occurred during the LV mode of State 1 operation.

The switchback counter is compared to a transition threshold at block720. If the switchback counter reaches the transition threshold, the VTevidence is compared to a termination threshold (block 722). Thetermination threshold is defined as a value less than the detectionthreshold and is used to determine when the accumulated VT evidence nolonger meets a level indicating a concerning heart rhythm. If the VTevidence counter is below the termination threshold, a VT episode mayhave never occurred or a non-sustained VT episode may have occurred andspontaneously terminated.

If either of the NF or the FF HRs are currently less than an SVTdetection limit (block 724), the combined evidence of the switchbackcount of consistently slow beats, low accumulation of VT evidence, and aHR estimate below an SVT detection limit results in a transition back tothe unconcerned State 1 at block 726. If any one of these transitioncriteria is not met, the detection algorithm remains in State 2 (block730).

Returning to block 712, if State 2 was not entered from the LV mode ofoperation in State 1 (i.e., State 2 was entered from the HV mode), theRRI variability is analyzed at block 732. In order to enter State 2 fromthe HV mode of operation, a sudden decrease in variability accompaniedby an increase in HR was detected. If the RRI variability has againincreased, the current heart rhythm may no longer be a concerningrhythm. An expected RRI range may not be stored when State 2 was enteredfrom the HV mode of State 1. The expected RRI range may not be updatedduring the HV mode due to the high variability of RRIs causing a wideexpected range. As such, RRI variability is examined for controllingtransition from State 2 back to State 1 when State 2 was entered fromthe HV mode of State 1.

An increase in RRI variability may be detected at block 732 by comparingone or more of the most recent RRI differences between two consecutivebeats to a mean of the most recent RRIs. If an average or other metricof the most recent RRI differences is greater than a predeterminedpercentage (e.g. approximately 20%) of the mean of the RRIs, an increasein RRI variability is detected at block 732.

If the RRI variability is increased, the current RRI is compared to thetachycardia expected RRI range at block 734. As described above, uponentering State 2, a tachycardia expected RRI range is initiated andupdated on a beat by beat basis using the current RRI and a previousRRMEAN and RRMAD. If the current RRI is longer than the tachycardiaexpected RRI range (block 734), the detection algorithm transitions tothe unconcerned State 1 (block 726) in response to the increased RRIvariability and RRI outside (slower than) the tachycardia expectedrange.

If the criteria for switching back to State 1 when State 2 was enteredfrom the HV mode are not met at blocks 732 and 734, the switchbackcounter is decreased at block 708. The slow beat counter is decreased atblock 710. The switchback and slow beat counters are decreased inresponse to the current RRI being equal to or shorter than the detectionlower limit interval, indicating the current rhythm remains a concerningrhythm.

In summary, evidence of RRIs that are consistently longer than thedetection lower limit, within or longer than an expected RRI range for anormal rhythm, longer than a tachycardia expected range, low accumulatedVT evidence, and/or increased RRI variability during State 2, or anycombination thereof may be used to control the transition from theconcerned State 2 to the unconcerned State 1.

Referring again to block 704, if the VT evidence reaches a detectionthreshold, for example if the VT evidence count reaches 6 or anotherpredefined detection threshold, a transition to the convinced State 3(block 740) occurs. Additionally, when both the FF and NF HR estimatesexceed an SVT rate limit and both the FF and NF EGM signals areclassified as treatable based on the noise/artifact rejection analysis,a transition to State 3 at block 740 may occur regardless of the VTevidence count.

During State 3, a therapy selection process is executed at block 742 todetermine what therapy, if any, should be delivered in response to thedetected VT. VT evidence accumulation continues at block 744 in the samemanner as in State 2. Depending on the therapy decision process andtherapy selected, there may be a time delay between entering State 3 andthe onset of therapy delivery. During that time, VT evidenceaccumulation continues so that a spontaneous termination of the detectedVT or a pause in the rhythm may be recognized.

The VT evidence counter is compared to a termination threshold at block746, which is defined to be a value less than the detection threshold.In one embodiment, the detection threshold is 6 and the terminationthreshold is 2. If the VT evidence counter reaches the terminationthreshold, and either the NF or FF HR falls below a SVT rate limit(block 748), the detection algorithm may transition from State 3 back toState 2. The termination threshold is not to be interpreted as athreshold for detecting a tachycardia episode termination but rather athreshold for detecting a need to transition to a lower detection state.

Before transitioning to State 2 from State 3, the slow beat counter maybe adjusted and examined to determine if a transition directly fromState 3 back to State 1 is warranted. If the current RRI is longer thanthe detection lower limit interval (block 752), the slow beat counter isincreased at block 756. The slow beat count is compared to a statechange threshold at block 758. If the slow beat counter reaches a State1 change threshold, a transition directly to State 1 occurs (block 726).The combined information of low VT evidence (block 746), the current RRIlonger than the detection lower limit interval (block 752), andconsistent slow beats based on the slow beat count (block 758) warrantsa transition to the unconcerned State 1.

If the State 1 change threshold has not been reached at block 758, therhythm is still considered a concerning rhythm. The detection algorithmtransitions back to State 2 at block 702.

On the other hand, if the current RRI is shorter than or equal to thedetection lower limit at block 752, the slow beat counter is decreasedat block 754. A transition back to the concerned State 2 is made basedon the low VT evidence and the NF or FF HR being below an SVT rate limitbut the current RRI still shorter than the detection lower limitinterval. Additional monitoring is performed in State 2 before returningto State 1, or progressing again into State 3.

After a therapy decision has been made at block 742, the detectionalgorithm advances to State 4 (block 750) if the accumulated VT evidenceremains above the termination threshold (negative result at block 746).In State 4, the therapy is delivered as scheduled at block 766. Upontherapy delivery, the VT evidence counter is cleared to a zero value atblock 768.

When the therapy being delivered is a shock therapy, the FF EGM signalmay be unreliable for several seconds. A FF unreliable timer may be setat block 770 to an interval of time to allow post-shock polarizationartifact to diminish before the FF EGM signal is used again fortachycardia detection. Similarly, any time a shock pulse or any othertherapy is delivered for therapeutic of diagnostic purposes, such asT-wave shocks for inducing VF, a FF unreliable timer may be set. The FFunreliable timer may be set, for example, to an interval ofapproximately 2 to 5 seconds. Similarly, if electrodes used in sensingthe NF signal are used in delivering a therapy, such as a pacingtherapy, a NF unreliable timer may be set to allow polarization artifactand/or any NF EGM morphology changes to dissipate before using the NFsignal again for tachycardia detection.

A transition back to State 2 (block 702) immediately occurs followingtherapy delivery. The detection algorithm transitions to State 2 toallow continued monitoring of the rhythm. The rhythm immediately aftertherapy delivery is still considered a concerning rhythm since thetherapy may have not been successful or a VT episode may be recurring.As such, monitoring of the heart rhythm in State 2 occurs afterdelivering a therapy before returning to State 1 (or State 3 in the caseof a redetected, recurring or worsening VT).

FIG. 21 is a flow chart 950 of a post-therapy mode of operationperformed upon re-entering State 2 after delivering a therapy. In someembodiments, after delivering a therapy, the detection algorithm mayoperate differently than the pre-therapy State 2 and State 3 operations.Unique criteria for redetection of the VT episode and criteria fordetecting termination of the VT episode after delivering a therapy maybe applied during a post-therapy mode of operation in State 2.

At block 951, a therapy is delivered in State 4 and a transition is madeback to State 2 into a post-therapy mode of operation (block 952). Uponentering State 4, the tachycardia expected range is no longer updated.The last computed tachycardia expected range prior to therapy deliveryis stored at block 954 for use in applying criteria for redetecting thetachycardia as will be further described below. In some embodiments,only the mean RRI used in setting the tachycardia expected range isstored at block 954 as threshold RRI for use in redetecting tachycardia.

As described in conjunction with FIG. 20, a FF EGM unreliable timer maybe set when the delivered therapy is a shock therapy such that the FFEGM signal is not used, at least initially, during the post-therapy modeof operation. Instead, the NF EGM signal is used for sensing cardiacevents for determining RRIs, setting a morphology analysis window andfor determining an overall morphology score and corresponding morphologyscore zone for adjusting the VT evidence counter post-therapy. If thedelivered therapy is a pacing therapy, i.e. anti-tachycardia pacing(ATP) therapy, the FF EGM signal may continue to be used for determiningan overall morphology score. As such, during the post-therapy mode,different signal processing methods may be used depending on the type oftherapy that was delivered.

At block 956, an overall morphology score is determined from the FF EGMsignal (post-ATP) or the NF EGM signal (post-shock) based on an analysiswindow set for the current NF sensed event on a beat-by-beat basis. Eachmorphology score is classified according to the morphology matchingzones as described previously. The VT evidence counter is updated atblock 958 based on the morphology score zone.

In some embodiments, specific beat feature rules are not applied duringthe post-therapy mode when the delivered therapy is a shock therapy. Inparticular, any rules relying on features determined from the FF EGM arenot applied post-shock, at least not until the FF unreliable timer isexpired or until a normal “pre-therapy” operating mode is re-enteredafter detecting termination. The VT evidence counter is adjusted basedonly on the NFMS zone post-shock.

Alternatively, a limited number of beat feature rules are appliedpost-shock. In one embodiment, a normal beat rule, analogous to the FFnormal beat rule described in conjunction with FIG. 13C above, is theonly zone-specific rule that is applied post-shock before adjusting theVT evidence counter. The normal beat rule may be applied using onlyspecific NF beat features, or using FF beat features after a FFunreliable timer expires, when the overall morphology score falls intothe VT gray zone. If the normal beat rule is true, the VT evidencecounter may be decreased instead of being increased in response to theoverall morphology score being in the VT gray zone (or increased but bya smaller increment than when the normal beat rule is false).

Additionally or alternatively, a rule analogous to the rhythm breakingpoint rule described previously may be applied across one or moremorphology zones during the post-therapy mode of operation. For example,if a long NF RRI is detected, and the morphology score ending the longRRI falls into the SVT confident zone, or is greater than another rhythmbreaking point detection threshold, a rhythm breaking point may bedetected. If a rhythm breaking point is detected, the VT evidencecounter is cleared at block 958. Similarly, if two consecutivemorphology scores are in the SVT confident zone, the VT evidence countermay be cleared at block 958.

After adjusting the VT evidence counter, the post therapy NF HR isestimated at block 960. The NF HR may be estimated, as described above,based on the nth shortest RRI out of a predetermined number of mostrecent RRIs occurring after the therapy delivery. The earliestpost-therapy NF HR estimate can be determined starting with the nthavailable beat. For example, if the ninth shortest RRI out of the mostrecent 12 RRIs is to be used as a HR estimate, the shortest RRIidentified after 9 RRIs following the therapy is the first NF HRestimate. Updating of the VT evidence counter can begin on abeat-by-beat basis prior to the nth post-therapy RRI.

The criteria for redetection and/or termination detection applied duringthe post-therapy mode of operation are dependent on the NF HR estimate.As such, the NF HR estimate is compared to an SVT rate limit at block962. If the NF HR is faster than the SVT limit, and the NF signal is notcorrupted (block 964), the tachycardia episode is redetected at block966 in response to the high HR. A transition to the convinced State 3occurs at block 968. If the post-therapy mode was entered after ATPtherapy, the FF EGM signal may be used for verifying a NF HR estimate asdescribed above. If the FF EGM signal is being used during thepost-therapy mode, e.g., post-ATP, the FF signal may also be verified asbeing non-corrupted at block 964 before transitioning to State 3.

The detection algorithm continues to update the VT evidence counter on abeat-by-beat basis during State 3 at block 968 according to thepost-therapy operation mode while making a therapy selection. The NF HRestimate is also updated during State 3 for detecting termination of thetachycardia episode during State 3. Thus, during the post-therapyoperation of State 3, a transition directly back to State 1 may occur iftermination criteria, e.g. consistent RRIs longer than the detectionlower limit interval, are met before a therapy decision is made andtherapy delivery is ready.

Referring again to block 962, if the NF HR estimate is less than the SVTlimit, but is greater than the sudden change limit, as determined atblock 974, the VT evidence counter is compared to the detectionthreshold at block 976. The tachycardia episode is redetected at block966 if the VT evidence counter is greater than the detection threshold(block 976) and the NF signal (and FF signal post-ATP) is not corrupted(block 964).

Termination of the tachycardia episode cannot be detected if the NF HRis greater than the sudden change limit. The detection algorithm willremain in the concerned State 2 (or State 3). As such, when the NF HR isgreater than the SVT limit (block 962), or less than the SVT limit butgreater than the sudden change limit (block 974), redetection criteriaare applied at blocks 976 and/or 964, but termination detection criteriaare not applied. If redetection criteria are not met (negative branchesof blocks 976 and 964), the process returns to block 956 to sense thenext cardiac event and determine the next overall morphology score zone,update the VT evidence counter and update the estimated NF HR.

In order for the redetection criteria to be met when the NF HR isgreater than the SVT limit or greater than the sudden change limit, theNF signal (and FF signal when being relied upon for adjusting VTevidence) should be non-corrupted. The NF and FF signals may bedetermined to be corrupted or non-corrupted at block 964 according tothe status of a “treatable rhythm” flag as described in conjunction withFIG. 19.

If the NF HR estimate is less than the sudden change limit (negativeresult at block 974), but greater than the tachycardia detection lowerlimit (block 980), both termination detection criteria and redetectioncriteria are applied. At block 982, termination detection criteria mayinclude a comparison of the current RRI to a detection lower limitinterval. Termination detection may also require that the detectionalgorithm has been operating in State 2 or State 3 for a total of atleast n seconds, for example approximately 3 seconds, to avoid frequentstate transitions. In response to termination detection criteria beingsatisfied at block 982 for the current RRI, a termination counter isincreased at block 988.

FIG. 22 is a flow chart 1001 of one method for detecting post-therapy VTtermination according to one embodiment. The method shown in FIG. 22 maycorrespond to operations performed at block 982 of FIG. 21 for applyingtermination detection criteria. When the NF HR estimate is less than thesudden change limit (block 1002), but greater than the detection lowerlimit, termination criteria are applied by comparing the current RRI tothe normal expected RRI range at block 1004. The normal expected RRIrange is the final expected RRI range stored upon transitioning from theunconcerned State 1 to concerned State 2 prior to the VT episodedetection. If the current RRI is within (or longer than) the normalexpected range at block 1004, a termination beat counter is increased atblock 1008.

If the current RRI is not within or longer than the normal RRI range,the current RRI may alternatively be compared to the detection lowerlimit interval at block 1006. If State 1 was exited during the HV modeof operation, a normal expected RRI range may not be stored. In thiscase, the threshold of the detection lower limit interval may be used atblock 1006 instead of a comparison to the expected RRI range at block1004.

If the current RRI is greater than at least one of the last storedexpected RRI range or the detection lower limit interval, thetermination beat counter is increased at block 1008. If neither of theconditions tested at blocks 1004 and 1006 are met, the termination beatcounter is decreased at block 1010.

The termination beat counter may be increased by one or anotherincrement each time the current RRI is in or longer than the last storedexpected RRI range or longer than the detection lower limit interval.The termination beat counter may be decreased by two or anotherdecrement each time the current RRI is shorter than the normal expectedRRI range or the detection lower limit interval.

If the termination counter is increased at block 1008, and at least nseconds have expired while operating in the current detection algorithmstate (State 2 or State 3), as determined at block 1014, additionaltermination criteria are applied. If the detection algorithm has notbeen operating in the current state for at least n seconds, for exampleapproximately 3 seconds, termination will not be detected. The requiredtime interval for operating within the current state may be applied atblock 1014 to prevent frequent state transitions. The algorithm mayproceed to apply redetection criteria at block 1012 when terminationcriteria are not met. Referring briefly to FIG. 21, when terminationcriteria are not met at block 982, the process advances to block 984 ofFIG. 21 to apply redetection criteria.

In FIG. 22, if the required time interval in the current state hasexpired at block 1014, the VT evidence counter is compared to atermination threshold at block 1016. If the VT evidence counter hasfallen below a selected threshold for VT evidence, the termination beatcounter is compared to termination beat threshold at block 1018. If thetermination beat counter has reached a threshold count, termination isdetected at block 1020. Termination is detected in response to the lowVT evidence and the RRIs being consistently within or longer than theexpected RRI range or longer than the detection lower limit interval.

If the VT evidence counter or the termination beat counter does not meeta respective termination detection threshold, additional terminationcriteria may be applied at blocks 1024 and 1026. The current NF HRestimate is compared to the HR corresponding to the last storedtachycardia expected range at block 1024. In one embodiment, if the nthshortest RRI out of the most recent m post-therapy RRIs is at least 50ms longer than the tachycardia expected range at block 1024, terminationmay still be detected if a pattern of variable RRIs is detected at block1026. A serious VT can be characterized by RRIs that are highly regularor stable in length. As such, termination detection criteria can includea criterion related to detecting instable RRIs as an indication of areturn to a non-pathological rhythm.

In one embodiment, the cumulative sum of consecutive RRI differences fora selected number of the most recent post-therapy RRIs is compared to apercentage of the mean of the same RRIs. For example, if the cumulativesum of the RRI differences is greater than at least approximately 10% ofthe mean RRI, the RRIs are considered instable, an indication of anon-treatable rhythm.

This RRI instability combined with a HR less than the tachycardiaexpected range is considered evidence that the VT has been terminatedsuccessfully by the delivered therapy. Termination is detected at block1020. If the criteria applied at blocks 1024 and 1026 for detecting VTtermination are not met, the algorithm applies redetection criteria atblock 1028.

Referring to FIG. 21, when the termination detection criteria are met atblock 982, termination is detected at block 992, and a transition tounconcerned State 1 occurs at block 994. If termination detectioncriteria are not met at block 982, the detection algorithm advances toblock 984 to apply redetection criteria.

FIG. 23 is a flow chart 1100 of one method for redetecting VT during apost therapy mode of operation when the NF HR is greater than thetachycardia detection lower limit but less than the sudden change limit(block 1102). This method for redetection of a VT may be applied atblock 984 of FIG. 21.

At block 1104, the VT evidence counter is compared to a detectionthreshold. If the detection threshold has not been reached, redetectiondoes not occur on the current beat. The algorithm advances to the nextbeat at block 1108. If the VT evidence counter is equal to or greaterthan the detection threshold, but the NF EGM signal (or FF EGM signalpost-ATP) is corrupted (negative branch of block 1106), redetectioncriteria are not met for the current beat. Corruption of the NF EGMsignal may be identified based on the status of the “treatable rhythm”flag as described in conjunction with FIG. 18. Referring briefly to FIG.21, the algorithm advances to the next beat by returning to block 956 todetermine the next NFMS and NF HR estimate for applying redetectionand/or termination criteria according to the next NF HR estimate asappropriate.

In FIG. 23, when the VT evidence counter has reached a detectionthreshold at block 1104 and the NF EGM signal is non-corrupted at block1106, the current RRI is compared to the last stored expected RRI rangeat block 1110 and/or the detection lower limit interval at block 1112.When State 1 was exited during the LV mode of operation, an expected RRIrange is stored for use in the comparison at block 1110. If State 1 wasexited during the HV mode, the detection lower limit interval is used asa threshold for the comparison at block 1112 for redetection. If thecurrent RRI is not shorter than the normal expected RRI range or theinterval corresponding to the tachycardia detection lower limit, the VTis not redetected on the current beat. The detection algorithm advancesto the next beat at block 1108.

If the current RRI is shorter than the normal expected range and/orshorter than the tachycardia detection lower limit interval, acoefficient of RRI instability is computed at block 1114. Thecoefficient of RRI instability is computed as a metric of the differencebetween the current RRI and a selected number of preceding post-therapyRRIs. The RRI stability metric computed for detecting termination asdescribed in conjunction with FIG. 22 is based on consecutive RRIdifferences and is not dependent on trend in HR. The coefficient of RRIinstability is computed using non-consecutive RRI differences and issensitive to a trend in heart rate.

In one embodiment, a coefficient of RRI instability is computed as thecumulative sum of the absolute difference between the current RRI andeach of the “a−1” most recent post-therapy RRIs divided by the mean ofthe “a” RRIs. This coefficient of RRI instability is compared to athreshold at block 1116. In one embodiment, the threshold applied to thecoefficient of RRI instability is approximately 0.6. If the coefficientof RRI instability is greater than a redetection threshold at block1116, redetection does not occur on the current beat and the algorithmadvances to the next beat at block 1108.

If the ratio of the sum of absolute RRI differences to the mean of theRRIs is less than a threshold, the RRIs are considered highly stable andan indicator of a possibly serious VT. VT is redetected at block 1120 inresponse to the VT evidence remaining above a detection threshold, theNF EGM signal being non-corrupted, the current RRI being shorter than anRRI expected range or detection lower limit interval, and highly stableRRIs. In some embodiments, an additional requirement of the NF HRfalling within than the last stored tachycardia expected range, must besatisfied at block 1118 in order to redetect the VT at block 1120.

Referring again to FIG. 21, if redetection criteria are met at block984, and the NF signal is not corrupted (block 964), VT is redetectedand a transition to convinced State 3 occurs at block 968.

The final HR condition used for selecting redetection/terminationcriteria during the post-therapy mode is a NF HR that is less than thetachycardia detection lower rate limit (negative branch of block 980).In this case, the current RRI is compared to the detection lower limitinterval at block 982. If the current RRI is not less than the detectionlower limit interval, a termination beat counter may be decreased (orkept at a zero count) at block 984. The process advances to the nextbeat by returning to block 956.

When the current RRI is greater than the detection lower limit interval,at block 982, the termination beat counter is increased at block 988 forthe current beat. The termination beat counter is then compared to athreshold for detecting termination at block 990. If the terminationbeat threshold has not been reached, termination is not detected for thecurrent beat. The process advances to the next beat by returning toblock 956.

If the termination beat counter has reached a threshold for detectingtermination at block 990, termination is detected at block 992. The VThas been successfully terminated by the delivered therapy. A transitionback to state 1 occurs at block 994. A termination threshold applied toa termination beat counter may set to approximately 5 or anotherselected number such that termination may be detected in as few as thethreshold number of beats post-therapy when each successive RRI islonger than the detection lower limit interval. In some embodiments, afixed number of RRIs immediately following the therapy delivery, forexample 2 to 3 post-therapy RRIs, may be ignored for the purposes ofredetection and/or termination detection.

When the post-therapy mode is entered after shock delivery, variousmethods may be used to control when use of the FF EGM signal isrestored. Recall that the post-therapy operating mode relies only uponthe NF EGM signal when a shock has been delivered. The FF EGM signal maynot return to a baseline, pre-therapy morphology for several seconds oreven one or more minutes after delivering a shock therapy. A return tocombined FF and NF signal processing which employs both signals forcontrolling state transitions may occur automatically upon detectingtermination.

In other embodiments, the restoration of FF EGM signal processing may beindependent of whether termination/redetection has occurred. In someembodiments, a fixed amount of time may be defined for ignoring the FFEGM signal. In this case, the NF EGM signal is used during thepost-therapy mode until the timer expires. Upon expiration of the timer,combined FF and NF EGM signal processing is resumed. Timer expirationmay occur before or after redetection or termination is detected andcorresponding state transition. Restoration of combined FF and NF EGMsignal processing is not necessarily dependent, therefore, on thedetection algorithm state. In another embodiment, FF EGM signalprocessing may be restored when either termination is detected or atimer expires, whichever occurs first, or both may be required.

Alternatively, further analysis of the FF EGM signal at block 995 isperformed to control when dual EGM signal processing is restored.Criteria may be applied to the FF EGM signal for determining when to usethe FF EGM signal again. For example, the restoration of FF EGM signalanalysis in addition to the NF EGM signal analysis may require a certainnumber of beats having a FFMS falling into the SVT confident zone asdetermined at block 995. Other criteria may be used for determining thatthe FF EGM signal has returned to pre-shock baseline morphology forcontrolling the transition from the post-shock NF-only signal processingto dual signal FF and NF EGM signal processing.

In one embodiment, after a FF unreliable timer expires after therapydelivery, the FFMS may be determined on a beat by beat basis forcounting the number of beats having a normal or near normal morphology(e.g., FFMS falling into the SVT confident zone or whole SVT zone). Whenthe FF EGM signal consistently demonstrates a normal or near-normalmorphology, which may be tracked using a counter that is increased ordecreased in response to the FFMS, restoration of FF signal processingmode may occur, regardless of the current detection algorithm state.

If termination is detected at block 990, resulting in a transition backto unconcerned State 1 at block 994, but the FF EGM signal has notreturned to a baseline morphology (block 995), the detection algorithmmay continue to operate using only the NF EGM signal (block 996). Onlythe NF EGM signal will be used to detect a sudden change in State 1.Once the FF EGM signal has returned to a baseline morphology, thedetection algorithm returns to a “pre-therapy” operating mode whichrelies on both the NF and the FF EGM signal processing (block 998) forcontrolling state transitions.

It is to be understood that termination detection may not be requiredfor restoring the FF EGM signal processing as shown in FIG. 21. If theFF EGM morphology is found to return to a baseline morphology while thedetection algorithm remains in State 2 or State 3, the detectionalgorithm may begin using the FF EGM signal in addition to the NF EGMsignal for applying beat feature rules, updating the VT evidence counterand controlling state transitions even before termination is detected.

In summary, in a pre-therapy mode, both FF and NF EGM signal processingoccurs and detection algorithm criteria are applied to both the FF andNF signals for controlling the various state transitions. In apost-therapy mode, criteria for detecting termination (and transitionfrom State 2 or State 3 to State 1) and criteria for redetection(transition from State 2 to State 3) are used which may be defineddifferently than the criteria used for controlling state transitionspre-therapy. Additionally, within the post-therapy mode, the signalprocessing methods used will depend on the type of therapy delivered.Post-ATP, both FF and NF signals may be used when applying terminationand redetection criteria. Post-shock, however, only NF EGM signals areused until criteria are met for restoring the use of the FF EGM.

Once termination is detected and the FF EGM signal processing has beenrestored, the detection algorithm can be said to be operating in apre-therapy mode again. If termination is not detected after a therapy,the detection algorithm may remain in the post-therapy mode, potentiallyredetecting and delivering another therapy one or more times, untiltermination criteria are met. Restoration of FF EGM signal processingmay occur at any time during the post-therapy mode when a FF unreliabletimer expires, morphology criteria are met, or other required conditionsare met. If termination is detected but criteria for restoring the FFEGM signal are not met, only NF EGM signal processing continues but thevarious “pre-therapy” criteria and rules for controlling statetransitions are used again by the detection algorithm rather than thepost-therapy termination and redetection criteria. The detectionalgorithm returns to a full “pre-therapy” mode of operating once bothtermination is detected and FF EGM signal processing is restored.

In the various flowcharts presented and described herein, multiplecriteria are sometimes described as being applied for controlling aresponse. A response may include adjusting a counter, transitioning to adifferent detection algorithm state, switching a detection algorithmmode within an algorithm state, setting a flag, setting a timer, oranother response. It should be recognized that when multiple criteriaare described as being required to be satisfied in order to provide aparticular response, various embodiments of the methods described hereinmay apply the described criteria individually (a single criterion) or inany combination for the purposes of controlling the particular response.Furthermore, in some cases the order of applying multiple criteria maybe changed from the particular order of applied criteria described inthe flowcharts presented herein. It is contemplated that where multiplecriteria are described for controlling a particular response, any subsetor combination of those criteria may be applied before providing theresponse.

Thus, a method and apparatus for detecting and discriminatingtachycardia have been presented in the foregoing description withreference to specific embodiments. It is appreciated that variousmodifications to the referenced embodiments may be made withoutdeparting from the scope of the disclosure as set forth in the followingclaims.

The invention claimed is:
 1. A medical device for discriminating cardiacevents, comprising: a subcutaneously implantable lead having a leadbody; a subcutaneously implantable housing electrically coupled to thelead body; a plurality of subcutaneously implantable electrodespositioned along the lead body and the housing to sense a first cardiacsignal and a second cardiac signal; and a processor within the housingconfigured to: determine a first match score corresponding to a beatwithin the first cardiac signal; determine within which one of aplurality of match zones the first match score is, wherein the pluralityof match zones includes a first match zone corresponding to a first,non-treatable cardiac event, and a second match zone corresponding to asecond, treatable cardiac event different from the first cardiac event;determine a second match score corresponding to the beat within thesecond cardiac signal; determine within which one of the plurality ofmatch zones the second match score is; determine an amount to increaseor decrease an event counter based on both within which of the pluralityof match zones the first match score is and within which of theplurality of match zones the second match score is; adjust the eventcounter by the determined amount; determine whether a current cardiacevent that includes the beat is a treatable cardiac event or anon-treatable cardiac event based on the adjusted event counter; andcontrol the medical device to deliver therapy in response to determiningthat the current cardiac event is the treatable cardiac event.
 2. Thedevice of claim 1, wherein the first match score corresponds to amorphology of the first cardiac signal and the second match scorecorresponds to a morphology of the second cardiac signal.
 3. The deviceof claim 1, wherein the first cardiac signal corresponds to a far fieldsensing vector formed between electrodes of the plurality of electrodesand the second cardiac signal corresponds to a near field sensing vectorformed between electrodes of the plurality of electrodes.
 4. The deviceof claim 3, wherein the first match zone has a first correlation withthe, first non-treatable cardiac event, and the plurality of match zonesfurther comprises a third match zone that has a second correlation withthe first, non-treatable cardiac event less than the first correlation.5. The device of claim 4, wherein the first, non-treatable cardiac eventcorresponds to supraventricular tachycardia and the second, treatablecardiac event corresponds to ventricular tachycardia.
 6. The device ofclaim 4, wherein the processor is configured to: decrease the eventcounter by a first value based on the first match score being in thefirst match zone and the second match score being within one of thefirst match zone and the third match zone; and decrease the eventcounter by a second value less than the first value based on the firstmatch score being in the first match zone and the second match scorebeing in the second match zone.
 7. The device of claim 4, wherein theprocessor is configured to: increase the event counter based on thefirst match score being in the third match zone and the second matchscore being in the second match zone; and decrease the event counterbased on the first match score being in the third match zone and thesecond match score being within one of the first match zone and thethird match zone.
 8. The device of claim 4, wherein the processor isconfigured to determine beat features of the first cardiac signal inresponse to the first match score being in the third match zone, andadjust the first match score in response to the determined beatfeatures.
 9. The device of claim 4, wherein the second match zone has afirst correlation with the second, treatable cardiac event, wherein theplurality of match zones further comprises a fourth match zonecorresponding to the second, treatable cardiac event, and wherein thefourth match zone has a second correlation with the second, treatablecardiac event greater than the first correlation with the second,treatable cardiac event.
 10. The device of claim 9, wherein theprocessor is configured to: decrease the event counter based on thefirst match score being in the third match zone and the second matchscore being in the fourth match zone; and increase the event counterbased on the first match score being in the third match zone and thesecond match score not being in the fourth match zone.
 11. The device ofclaim 9, wherein the processor is configured to: increase the eventcounter by a first value based on the first match score being in thefirst match zone and the second match score being in the first matchzone; and increase the event counter by a second value less than thefirst value based on the first match score being in the first match zoneand the second match score being in one of the second match zone, thethird match zone and the fourth match zone.
 12. The device of claim 9,wherein the first, non-treatable event corresponds to a supraventriculartachycardia event and the second, treatable cardiac event corresponds toventricular tachycardia.
 13. The device of claim 9, wherein theprocessor is configured to determine beat features of the first cardiacsignal in response to the first match score being in the third matchzone, and adjust the first match score in response to the determinedbeat features.
 14. A method for discriminating cardiac events with amedical device comprising a subcutaneously implantable lead having alead body, a subcutaneously implantable housing electrically coupled tothe lead body, a plurality of subcutaneously implantable electrodespositioned along the lead body and the housing to sense a first cardiacsignal and a second cardiac signal, and a processor within the housing,the method comprising: determining, by the processor, a first matchscore corresponding to a beat within the first cardiac signal;determining, by the processor, within which one of a plurality of matchzones the first match score is, wherein the plurality of match zonesincludes a first match zone corresponding to a first, non-treatablecardiac event, and a second match zone corresponding to a second,treatable cardiac event different from the first cardiac event;determining, by the processor, a second match score corresponding to thebeat within the second cardiac signal; determining, by the processor,within which one of the plurality of match zones the second match scoreis; determining, by the processor, an amount to increase or decrease anevent counter based on both within which of the plurality of match zonesthe first match score is and within which of the plurality of matchzones the second match score is; determining, by the processor, whethera current cardiac event that includes the beat is a treatable cardiacevent or a non-treatable cardiac event based on the adjusted eventcounter; and controlling, by the processor, the medical device todeliver therapy in response to determining that the current cardiacevent is the treatable cardiac event.
 15. The method of claim 14,wherein the first match score corresponds to a morphology of the firstcardiac signal and the second match score corresponds to a morphology ofthe second cardiac signal, wherein the first cardiac signal correspondsto a far field sensing vector formed between electrodes of the pluralityof electrodes and the second cardiac signal corresponds to a near fieldsensing vector formed between electrodes of the plurality of electrodes,and wherein the first, non-treatable cardiac event corresponds tosupraventricular tachycardia and the second, treatable cardiac eventcorresponds to ventricular tachycardia.
 16. The method of claim 14,wherein the first match zone has a first correlation with the first,non-treatable cardiac event and the plurality of match zones furthercomprises a third match zone that has a second correlation with thefirst, non-treatable cardiac event less than the first correlation. 17.The method of claim 16, wherein determining the amount to increase ordecrease the event counter and adjusting the event counter by thedetermined amount comprises: decreasing the event counter by a firstvalue based on the first match score being in the first match zone andthe second match score being within one of the first match zone and thethird match zone; and decreasing the event counter by a second valueless than the first value based on the first match score being in thefirst match zone and the second match score being in the second matchzone.
 18. The method of claim 16, wherein determining the amount toincrease or decrease the event counter and adjusting the event counterby the determined amount comprises: increasing the event counter basedon the first match score being in the third match zone and the secondmatch score being in the second match zone; and decreasing the eventcounter based on the first match score being in the third match zone andthe second match score being within one of the first match zone and thethird match zone.
 19. The method of claim 16, wherein the second matchzone has a first correlation with the second, treatable cardiac event,wherein the plurality of match zones further comprises a fourth matchzone corresponding to the second, treatable cardiac event, and whereinthe fourth match zone has a second correlation with the second,treatable cardiac event greater than the first correlation with thesecond, treatable cardiac event.
 20. The method of claim 19, whereindetermining the amount to increase or decrease the event counter andadjusting the event counter by the determined amount comprises:decreasing the event counter based on the first match score being in thethird match zone and the second match score being in the fourth matchzone; and increasing the event counter based on the first match scorebeing in the third match zone and the second match score not being inthe fourth match zone.
 21. The method of claim 19, wherein determiningthe amount to increase or decrease the event counter and adjusting theevent counter by the determined amount comprises: increasing the eventcounter by a first value based on the first match score being in thefirst match zone and the second match score being in the first matchzone; and increasing the event counter by a second value less than thefirst value based on the first match score being in the first match zoneand the second match score being in one of the second match zone, thethird match zone and the fourth match zone.